CN114074665A

CN114074665A - Method for operating an assistance system of a vehicle and assistance system of a vehicle

Info

Publication number: CN114074665A
Application number: CN202110918739.0A
Authority: CN
Inventors: M·扎尔费尔德; N·吉尔巴赫
Original assignee: Robert Bosch GmbH
Current assignee: Robert Bosch GmbH
Priority date: 2020-08-11
Filing date: 2021-08-11
Publication date: 2022-02-22
Also published as: DE102020210116A1

Abstract

The invention relates to a method for operating an auxiliary system of a vehicle, comprising the following steps: -sensing the surroundings of the vehicle, -generating at least two surroundings maps (2a, 2b) at different points in time, wherein each surroundings map (2a, 2b) is divided into a plurality of cells (3), -wherein each cell (3) is assigned a predefined value on the basis of the presence of an object (4) at a location of the surroundings (U) corresponding to the cell (3), -classifying an object (4) sensed in the surroundings (U) of the vehicle (10), -identifying a static object (4a) by means of the classification, and-comparing the at least two surroundings maps (2a, 2b) with one another, wherein the comparison is carried out in accordance with the respective cell (3) of the surroundings maps (2a, 2b) representing the static object (4 a). The invention also relates to an assistance system for a vehicle.

Description

Method for operating an assistance system of a vehicle and assistance system of a vehicle

Technical Field

The invention relates to a method for operating an auxiliary system of a vehicle and to an auxiliary system of a vehicle.

Background

Auxiliary systems for vehicles are known which generate a map of the surroundings, a so-called "occupancy grid map". In such a surrounding map, objects in the surrounding of the vehicle can be mapped. In general, a surrounding map is generated by means of environmental data sensed by an environmental sensing device of a vehicle. In particular, the environment data and the motion information having errors can cause deviations between the representation in the surrounding map and reality.

Disclosure of Invention

In contrast, the method according to the invention has the task of making it possible to provide a map of the surroundings with particularly precise and reliable information. This is achieved by a method for operation of an auxiliary system of a vehicle, comprising the steps of:

-sensing, in particular by means of an environment sensing device of a vehicle, a surrounding environment of the vehicle,

generating at least two surroundings maps at different points in time, in particular having in each case an imaging of the surroundings, wherein each surroundings map is divided into a plurality of cells, wherein each cell is assigned a predefined value based on the presence of an object at a location of the surroundings corresponding to the cell,

-classifying objects sensed in the surroundings of the vehicle,

-identifying static objects by means of said classification, and

-comparing at least two ambient maps with each other.

The comparison is carried out in accordance with the corresponding cells of the surroundings map which represent the static object.

In other words, in this method, two ambient environment maps, which may also be referred to as "occupancy grid maps" in particular, are generated based on the sensed ambient environment. Each ambient map is divided into a plurality of cells, to which predetermined values are respectively assigned. Here, a value is assigned to a cell based on whether an object is present at a location in the vehicle surroundings corresponding to the location of the particular cell. In particular, this enables positioning of the vehicle, preferably with respect to the object. For example, a value may be assigned to a cell as a value that preferably marks whether an object is present or not.

Objects sensed in the surrounding environment of the vehicle are classified. Here, the recognition and classification of objects into different categories is considered as classification. In particular, the objects are divided into static and movable (or non-static) objects. Next, objects classified as static are identified from the classified objects. Next, the following regions of the two surroundings maps are used for comparison of the two surroundings maps: static objects have been identified on the respective ambient locations of the area. Preferably, all other areas of the surroundings map are ignored here. Here, objects whose location in the surroundings does not change over time are considered to be static objects, such as buildings, walls, trees or other structural objects. This means that the comparison of the surroundings map is carried out on the basis of immobile objects which always have the same location in the surroundings, so that, for example, the relative position with respect to these objects can be determined particularly reliably.

Thus, the method provides the following advantages: the unmovable area of the surroundings is used for comparison of the surroundings map. For example, a previously generated first surroundings map in the same area can be compared and confirmed in a reliable and simple manner even when the time interval between driving through the surroundings in a specific area is large. This can be achieved particularly simply and reliably, since, for example, static objects do not change their position in the surroundings. Thus, a surroundings map with a particularly high accuracy can be provided, for example, in order to allow as high a positioning accuracy of the vehicle as possible in the surroundings map.

The contents of the preferred embodiments are preferred embodiments of the invention.

Preferably, the method further comprises the steps of: based on a comparison of at least two surroundings maps with one another, a vehicle is located in at least one of the surroundings maps. Preferably, for this purpose, the first sensing of the first surroundings map is carried out as a so-called "training", for example by means of a manual driver-controlled driving of the vehicle. Here, determining the position and orientation of the vehicle within the surroundings map is considered as a localization. For example, objects are mapped into a first surroundings map by means of a distance measurement method and an environment sensor of the vehicle. Later on, a second ambient map can be generated by means of a second sensing by a second travel in the same area of the ambient environment and compared with the first ambient map. Based on this comparison, the position of the vehicle can therefore be estimated, in particular with respect to objects or the like depicted in the surroundings map. Since the two surroundings maps are compared with one another on the basis of static objects, a particularly precise and reliable localization of the vehicle can be achieved.

Preferably, the method further comprises the steps of: cells representing static objects in the surrounding environment are prioritized. In this case, the at least two ambient maps are compared with one another by means of the prioritized cells. The prioritization of prioritized cells, for example, when evaluating the surroundings map, can be regarded as a priority. Particularly preferably, all cells of the surroundings map can be assigned a weighting factor, which is multiplied, for example, by the value of the cell. The prioritization may include an increase in the weighting factor, so that the values of those cells representing static objects are more important, for example, in the localization of the vehicle, as a result of which a higher accuracy of the obstacle map can be achieved.

Particularly preferably, the method further comprises the steps of: by means of the classification, movable objects in the surroundings of the vehicle are identified. In this case, those cells of the surroundings map which represent the movable object are excluded from the comparison of the at least two surroundings maps. Preferably, those cells representing movable objects are additionally excluded from the vehicle positioning step. This means that the following cells are not used for the comparison of the two surrounding maps: movable objects have been identified on the respective surroundings location of the cell. For example, these cells can be ignored in the comparison. For example, the cells can be assigned a predetermined, in particular additional, value which defines that the respective cell is not taken into account in the comparison. In this way, a particularly high degree of accuracy can be achieved when comparing the surroundings maps and when locating the vehicle in at least one of these surroundings maps, since information that is subject to possible errors due to different positions of the movable object at different points in time of recording the surroundings maps is not taken into account. Furthermore, the method can be carried out particularly simply and resource-effectively, since, for example, for the comparison step and in particular also for the positioning step, a smaller number of objects in the surroundings needs to be sensed and analyzed precisely.

Preferably, the method further comprises the steps of: those cells of the surroundings map which represent movable objects are neutralized (neutralieren). Here, "resetting the cell value to a standard value, in particular, a standard value existing before distribution" is considered to be neutralized. In particular, "resetting a cell in such a way that it represents the state" no object "is regarded as neutral. Alternatively, the cell can also be set to the state "occupied" by this neutralization, i.e., it can be set such that the cell is marked with an object. By neutralizing the cells for the recognized movable objects, the regions of the surroundings map representing the static objects can be highlighted in a particularly simple manner, so that an accurate comparison and an accurate localization can be achieved by simple and cost-effective means.

Preferably, the method further comprises the steps of: by means of the classification, traffic participants in the surroundings of the vehicle are identified. In this case, the identified traffic participant is recognized as a movable object. In this case, humans, animals and vehicles of any type, in particular those located in the surrounding area that can be traveled by means of the vehicle, are considered as traffic participants. Here, each of these objects is considered as a traffic participant, whether it is moving or stationary at the sensing time point. This means that, for example, a parked motor vehicle, whether or not a passenger is present, is recognized as a traffic participant and correspondingly recognized as a movable object.

It is further preferred that the sensing of the surroundings of the vehicle comprises generating camera imaging by means of a camera. In this case, the classification of the objects sensed in the vehicle surroundings is carried out by means of an evaluation of the camera image. The camera is preferably part of an environment sensing device of the vehicle. The classification can be carried out in a simple and reliable manner by the evaluation of the camera images generated by means of the camera.

Particularly preferably, the classification is carried out automatically by means of an evaluation unit. For example, the evaluation unit may be part of a control device of the vehicle or may alternatively be provided in addition to the control device. In particular, the evaluation unit can comprise an algorithm which is provided for analyzing the generated camera images for classifying and identifying the static object and the movable object from the camera images. For example, the evaluation unit can have artificial intelligence, by means of which the classification is carried out.

Preferably, the classification can be carried out and/or confirmed manually by means of a user input of the vehicle user, in particular by means of a human-machine interface, such as a display and/or input device. For example, the generated ambient camera images can be displayed to the user by means of a display and/or input device, wherein the user can select regions of the image and can mark these regions as static or movable. Alternatively or additionally, by means of a display and/or input device, it is possible to display: which regions have been classified as static or movable by the analysis evaluation unit. These areas can be confirmed or adapted by user input. This makes it possible to carry out the method in a manner that is verifiable and particularly reliable for the driver, since the correct classification function can be verified and, if necessary, adapted by interaction with the driver.

Preferably, the method further comprises the steps of: an L-shaped object in the vehicle surroundings is identified. Here, the identified L-shaped object is recognized as a static object. An object having two at least substantially straight faces which intersect at right angles or at an angle of preferably between 20 ° and 160 °, is to be regarded as an L-shaped object here, in particular in that the individual faces of these faces are arranged vertically. Such an L-shaped object refers to a structural construction such as a wall or a house, for example. By identifying such an L-shaped structure, it is therefore possible to identify in a particularly simple manner: in which regions of the surroundings static objects, i.e. non-movable objects, are present, without complicated analysis of the imaging of these objects, for example, being necessary.

In addition, the invention provides an auxiliary system of the vehicle. The assistance system comprises an environment sensing device arranged for sensing the surroundings of the vehicle and a control apparatus arranged for implementing the described method. In particular, the surroundings sensor device is also provided here for sensing range-finding data of the vehicle. In this case, the assistance system can be provided with a particularly low and cost-effective hardware complexity, in order to be able to operate the vehicle with high accuracy and high comfort for the driver.

Preferably, the environment sensing means of the auxiliary system comprise radar sensors and/or lidar sensors for sensing the surroundings. It is particularly advantageous to use radar sensors having a medium effective distance, for example in the range of up to a maximum of 50m, preferably up to a maximum of 25m, in particular at least 5 m. In this case, a surroundings map is generated on the basis of the environmental data sensed by means of the environmental sensor device and the vehicle is preferably also positioned in the surroundings map.

Particularly preferably, the environment sensor device of the auxiliary system also has a camera for sensing the surroundings and for generating a camera image of the surroundings. Preferably, the camera is a proximity camera, in particular a proximity camera arranged for sensing the surroundings in an area between 1m and 20m from the vehicle.

Preferably, the assistance system further comprises an analytical evaluation unit and/or an input device. The evaluation unit is provided for automatically classifying objects sensed in the surroundings of the vehicle. For example, the evaluation unit may be part of a control device of the vehicle or alternatively may be provided in addition to the control device. Alternatively or additionally, the classification can be carried out and/or confirmed by means of an input device, in particular by means of a manual input by the vehicle user.

Drawings

The present invention will be described with reference to the following examples, which are provided in conjunction with the accompanying drawings. In the figures, functionally identical components are designated by the same reference numerals, respectively. Shown here are:

FIG. 1 is a schematic simplified diagram of the operation of a vehicle having an auxiliary system in accordance with a preferred embodiment of the present invention, an

Fig. 2 shows a further schematic representation of the operation of the vehicle of fig. 1.

Detailed Description

Fig. 1 and 2 show a schematic, simplified diagram of a vehicle 10 with an assistance system 50. Here, a number of different simplified diagrams of a method for the operation of the assistance system 50 of the vehicle 10 are shown.

The assistance system 50 comprises an environment sensing device 52 arranged for sensing the surroundings U of the vehicle 10. The environment sensing means 52 comprise a radar sensor, a lidar sensor and a camera. By means of the environment sensing device 52, objects 4, for example in the form of obstacles, in the surroundings U of the vehicle 10 can be sensed, as is schematically shown in fig. 1(a), for example.

In addition, the assistance system 50 comprises a control device 51 arranged for generating a surroundings map 2, which is an image of the surroundings U, based on the sensed surroundings U, as shown in fig. 1 (b).

The surroundings map 2 is divided into a plurality of cells 3. The surroundings map 2 is two-dimensional and is formed in the plane of the roadway surface, on which the vehicle 10 can travel in the surroundings U. The cells 3 are square and have a side length of 1 m. The entire surroundings map 2 is likewise square and has ten parallel cells 3 in length and width, respectively, i.e. the surroundings map 2 reflects an area with 10m side lengths.

Based on the sensed object 4, each of the following cells 3 of the surroundings map 2 is assigned a predefined value: the cells are located at a location of the surroundings map 2 corresponding to the location of the surroundings U with the object 4. For example, a value representing the status "occupied" is assigned to the corresponding cell 3a representing the following place in the surrounding environment map 2: there is an object 4 at the site in the surrounding environment U (see fig. 1 (b)).

The vehicle 10 in the surroundings U can be located by means of the surroundings map 2. For this purpose, a second ambient map 2b is generated at a further point in time and compared with at least one further first ambient map 2 a. This is shown in simplified form in fig. 2 (c).

In this case, the vehicle 10 is first driven through the region of the surroundings U during a first training run, for example, under the manual control of the driver. During this training run, a first surroundings map 2a is generated. This is shown in fig. 2(a) and (b).

In a second step, a second surroundings map 2b can be generated, for example, when the vehicle 10 is again located in the same region of the surroundings U at a later point in time. In each of the two

surroundings maps

2a, 2b, all cells 3 are assigned a corresponding value in order to represent an object 4 or a free area in the surroundings U.

Next, in a further step, the two

surroundings maps

2a, 2b are compared with each other. This is schematically illustrated in fig. 2 (c). In this case, the two

surroundings maps

2a, 2b can be superimposed on the basis of those cells 3 which represent the specific object 4b, and the vehicle 10 in the surroundings U can thus be positioned with particularly high accuracy on the basis of the two

surroundings maps

2a, 2b during the second journey.

In the surrounding environment in which the vehicle 10 is moving, changes in the surrounding environment U may often occur over time. In the surroundings U, there may be movable objects 4b, such as other traffic participants, for example pedestrians and moving or parked vehicles (see fig. 2 (a)). Such a movable object 4b may be located at different points in time, for example, when creating the surroundings maps 2a, 2b, or may no longer be arranged within the same area of the surroundings U, for example, in the second sensing of fig. 2b of the second surroundings. In order to enable a simple and reliable function of the assistance system 50 even in such circumstances in which the surroundings are variable, the method for operating the assistance system 50 described below is implemented.

In this case, the objects 4 sensed in the surroundings U of the vehicle 10 are classified by means of the surroundings sensing device 52. The classification is performed by means of camera imaging sensed by the camera of the environment sensor device 52. Alternatively or additionally, the classification can also be carried out as a function of environmental data recorded by means of radar sensors and/or by means of lidar sensors. For this purpose, the camera images are analyzed by means of an evaluation unit 53 of the assistance system 50. Here, the sensed objects 4 are classified into a static object 4a and a movable object 4 b. For example, the pedestrian and the parked vehicle exemplarily shown in fig. 2(a) are identified and classified as the movable object 4b, respectively. In addition, the walls bounding the parking space in fig. 2(a) are identified and correspondingly classified as static objects 4 a.

In this case, the classification can be carried out in a particularly simple manner in such a way that L-shaped objects are searched for in the surroundings U and the recognized L-shaped objects are recognized as static objects 4 b. For example, the wall in fig. 2(a) can be easily identified as a static object 4b, depending on the fact that the side faces 41 intersect L-shaped, in this case at right angles.

After the classification of the object 4, the comparison of the two

ambient maps

2a, 2b is carried out in such a way that only those cells representing the static object 4a are considered. To simplify this process, the region 40b of the

surroundings map

2a, 2b representing the movable object 4b is neutralized (see fig. 2 (b)). This means that those cells 3b representing movable objects 4b are assigned a value indicating the state "unoccupied" or "no object". The respective cell 3b is thereby excluded from the comparison of the surroundings maps 2a, 2b and therefore also from the subsequent localization of the vehicle 10.

Here, the neutralization of the specific cell 3b representing the movable object 4b provides the following advantages: errors in the comparison and/or localization, for example, due to objects 4 that have moved slightly between the two points in time at which the corresponding

ambient maps

2a, 2b were generated, can be avoided. In particular, only the area of the surroundings maps 2a, 2b that is always located at the same point within the surroundings U is therefore left. The surroundings maps 2a, 2b can therefore be provided in a simple manner and with particularly high accuracy, so that a highest possible accuracy of the position determination of the vehicle 10 can be achieved by means of the surroundings maps 2a, 2 b.

Claims

1. Method for operating an auxiliary system (50) of a vehicle (10), the method comprising the steps of:

-sensing a surrounding environment (U) of the vehicle (10),

-generating at least two surroundings maps (2a, 2b) at different points in time, wherein each surroundings map (2a, 2b) is divided into a plurality of cells (3), wherein each cell (3) is assigned a predefined value on the basis of the presence of an object (4) at a location of the surroundings (U) corresponding to the cell (3),

-classifying objects (4) sensed in a surrounding environment (U) of the vehicle (10),

-identifying a static object (4a) by means of said classification, and

-comparing the at least two surroundings maps (2a, 2b) with each other,

wherein the comparison is performed in dependence of the corresponding cells (3) of the surroundings map (2a, 2b) representing static objects (4 a).

2. The method of claim 1, further comprising the steps of: locating the vehicle (10) in at least one of the surroundings maps (2a, 2b) on the basis of a mutual comparison of the at least two surroundings maps (2a, 2 b).

3. The method according to any of the preceding claims, further comprising the step of: prioritizing cells (3) representing static objects (4a) in the surroundings (U), wherein the comparison of the at least two surroundings maps (2a, 2b) with one another takes place by means of the prioritized cells (3).

4. The method according to any of the preceding claims, further comprising the step of:

-identifying a movable object (4b) in the surroundings (U) of the vehicle (10) by means of the classification, wherein those cells (4b) of the surroundings map (2a, 2b) representing a movable object (4b) are excluded from the comparison of the at least two surroundings maps (2a, 2 b).

5. The method of claim 4, further comprising the steps of:

-neutralizing those cells (3) of the surroundings map (2a, 2b) representing a movable object (4 b).

6. The method according to claim 4 or 5, further comprising the steps of:

-identifying traffic participants in the surroundings (U) of the vehicle (10) by means of the classification, wherein the traffic participants are recognized as movable objects (4 b).

7. The method according to any one of the preceding claims, wherein the sensing of the surroundings (U) of the vehicle (10) comprises generating camera imaging by means of a camera, and wherein the classifying is performed by means of an analytical evaluation of the camera imaging.

8. The method according to any one of the preceding claims, wherein the classification is carried out automatically by means of an analytical evaluation unit (53).

9. Method according to any of the preceding claims, wherein the classification can be implemented and/or confirmed manually by means of a user input of a user of the vehicle (10).

10. The method according to any of the preceding claims, further comprising the step of:

-identifying L-shaped objects in the surroundings (U) of the vehicle (10), wherein the identified L-shaped objects are recognized as static objects (4 a).

11. An assistance system of a vehicle (10), the assistance system comprising:

-an environment sensing device (52) for sensing the surroundings (U) of the vehicle (10), and

-a control device (51) arranged for implementing the method according to any one of the preceding claims.

12. Auxiliary system according to claim 11, wherein the environment sensing device (52) has a radar sensor and/or a lidar sensor for sensing the surroundings (U).

13. Auxiliary system according to claim 11 or 12, wherein the environment sensing device (52) has a camera for sensing the surroundings (U) and for producing camera imaging.

14. The assistance system according to any one of claims 11 to 13, further comprising an analytical evaluation unit (53) and/or an input device (54) to classify objects (4) sensed in the surroundings (U) of the vehicle (10).