DE102013018315A1 - Environment model with adaptive grid - Google Patents

Abstract

A method for providing an environment model for a vehicle comprises the steps of: receiving data from at least one sensor system for environment detection; Creating a grid map, as the environment model, based on the received data, the grid of the grid map consisting of a plurality of cells each representing an area of the environment of the vehicle; and adapting the representation of the environment by the grid map depending on a driving situation of the vehicle by changing the size and / or geometry of the areas of the environment represented by the cells, and / or by changing the arrangement of the cells in the grid of the grid map.

Description

The present invention relates to a method and a unit for providing an environment model for a vehicle.

Vehicles are increasingly being equipped with modern driver assistance and safety functions, which assist a driver in driving a vehicle, as well as being able to take over the guidance of the vehicle to an increasing extent in different situations. In order to realize these tasks, the vehicles are equipped with increasingly more and better environment sensors, which allow an ever better detection of the environment of the vehicle.

One task here is the recognition and tracking of static, generic objects that are detected with the aid of the various environmental sensors in the vicinity of the vehicle. For this purpose, grid-based approaches are increasingly being used, whereby the environment around the vehicle is subdivided in a grid or "grid" in a flat plane into square cells, which are filled depending on the sensor signal with busy or free information. This creates an occupancy map around the vehicle, which can be used in orientation and in the object recognition. Corresponding grid-based environment models are for example from the publications DE 10 2007 013 023 A1 . DE 10 2009 007 395 A1 . DE 10 2010 006 828 A1 . DE 10 2011 081 740 A1 and WO 2013/060323 A1 known.

The grid maps are selected world-wide, that is, with a coordinate system that has a fixed relation to the real world, so that the vehicle moves relative to the grid map. This has the advantage that the proper movement of the vehicle relative to the world does not result in the grid map having to be converted and transformed at each update cycle in accordance with the movement in the meantime carried out by the vehicle. This avoids the need for unnecessary transformation operations and allows more accurate results.

The grid maps are constructed as square grid maps of square cells. In this way, the fact is taken into account that the vehicle moves relative to the grid map and in particular can change the orientation of the vehicle over time as desired. Therefore, even if the vehicle changes its orientation by any angle relative to the world and thus also relative to the grid map, it can therefore be ensured that the grid map always covers a constant minimum area in front of the vehicle, corresponding to half the side length of the square grid map.

To enable efficient implementation, the grid map is constructed similarly to a two-dimensional ring buffer, with the rows or columns of the map running out of sight behind the vehicle being deleted and appended to the opposite side of the grid as corresponding new rows or columns.

This approach has proven particularly useful in complex inner-city scenarios. For example, with a grid of 500 x 500 cells and a size of the individual cells of 8 cm x 8 cm with a grid map, an area of 40 m x 40 m can be mapped, corresponding to an area of 20 m to each side of the vehicle.

For high speeds, such as driving on a highway at speeds of, for example, over 200 km / h, however, a much larger foresight is needed, which must be covered by the grid map, so that actuators and warnings can be controlled in time.

This requirement can be met by choosing a correspondingly larger grid with a correspondingly larger number of cells per column and row in order to achieve the desired look-ahead range. However, this has the disadvantage that the quadratic increase in the number of cells in the grid associated with the enlargement of the grid map leads to a correspondingly quadratic increase in storage requirements and computing time, which can be a problem even for current, high-performance computer platforms.

If, on the other hand, the number of cells of the lattice map is maintained in order to obtain a larger foresight size and the size of the individual cells is increased accordingly, for example to 16 cm × 16 cm or 20 cm × 20 cm, the necessary memory requirement and the computing time can be maintained, but by the price of a reduced resolution of the information that can be mapped in the grid map and, consequently, with a reduced suitability for use in complex inner-city scenarios.

It is therefore the object of the present invention to provide a method and a unit for providing an environment model for a vehicle, which overcomes the above disadvantages.

It is another object of the present invention to provide a method and a unit for providing an environment model for a vehicle indicate which are suitable for use in different application situations.

It is a further object of the present invention to provide a method and a unit for providing an environment model for a vehicle, which permit a large foresight range with high information quality and with low expenditure on computing requirements and storage space.

These and other objects of the present invention are achieved by a method and environment model unit as defined by claims 1 and 12. Further preferred embodiments are set forth in the dependent claims.

As a solution, a method is provided for providing an environment model for a vehicle, comprising the steps of: receiving data from at least one sensor system for environment detection; Creating a grid map, as the environment model, based on the received data, the grid of the grid map consisting of a plurality of cells each representing an area of the environment of the vehicle; and adapting the representation of the environment by the grid map depending on a driving situation of the vehicle by changing the size and / or geometry of the areas of the environment represented by the cells, and / or by changing the arrangement of the cells in the grid of the grid map.

With the present invention, it has been recognized that it is not necessary to work continuously with an always consistent grid configuration. Rather, this can be deviated from, and the grid configuration can be adapted to this in a variety of ways depending on a given driving situation. This opens up manifold possibilities for arranging and configuring a given number of cells in different ways in order to allow the best possible modeling in range and resolution of the area of the environment relevant for the vehicle or for driver assistance functions and other applications without unnecessary additional effort in memory and computing time to require.

The driving situation may include a speed of the vehicle, a road type, a lane course, a traffic density and / or a width of a roadway on which the vehicle is moving.

Preferably, the grid card is constructed substantially along the lane of the vehicle. In this way, only the area of the roadway on which the vehicle is moving or the travel path in which the vehicle is moving may be imaged in the grid map. The representation of the environment through the grid map can thus be concentrated on the area of the environment that has the highest relevance for the movement of the vehicle. Other areas of the environment, such as areas beyond the lane, may in this way be "hidden" and not displayed in the grid map as an environment model. This has the advantage that no attention needs to be paid to objects or events in those areas where no or at best only minimal impact or other relevance to driving the vehicle can be expected. Thus, computing time and memory can be saved.

Preferably, the cells of at least one row of the grid may represent a region which is delimited on two opposite sides by a curve which substantially corresponds to the course of the lane.

The curvature of the lane is thus used as a default to create a correspondingly curved lattice map. The grid map can be constructed following the actual course of the traffic lane. In this way it is also achieved that the cells are arranged according to the direction of movement of the vehicle. In other words, the vehicle travels substantially parallel to a longitudinal axis of the grid over the grid map, wherein the longitudinal axis is determined by the curve of the cell boundaries, as dictated by the lane course. In this way it is achieved that the grid map is always aligned substantially optimally relative to the orientation of the vehicle.

It is also possible for the cells of at least one row of the grid to represent an area whose extent is adjusted in the direction of vehicle movement, depending on the speed of the vehicle. Alternatively or additionally, it is also possible for the cells of at least one row of the grid to represent an area whose extent in the direction of vehicle movement is an integral multiple of the extent in the direction transverse to the vehicle movement.

The cells of the grid are hereby chosen to be longer than wide, thereby reducing the longitudinal resolution while maintaining the transverse resolution. This is possible because the vehicle always moves substantially along the longitudinal direction of the cells, and not in the transverse direction. In this way, with a constant number of cells correspondingly a larger foresight range can be achieved, or alternatively for a given desired look-ahead the number of cells in the grid can be reduced. Thus, computing time and memory can be saved.

If the length adjustment of the cells is dependent on the speed, for example by selecting a greater length at a higher speed, then the look-ahead range of the speed can also be adapted.

The adaptation preferably takes place in discrete steps, preferably in steps of doubling or halving.

If the adaptation takes place only in discrete steps, it is correspondingly less necessary to make an adjustment. Therefore, a conversion of the lattice card must be carried out correspondingly less frequently, as a result of which the errors arising due to conversion can be correspondingly reduced and the outlay, in particular of computing time, for the conversion can be reduced. The adaptation is particularly easy to implement if a change is chosen as a halving or doubling of the length or width of the cells. Thus, for example, when halving the cell length, each cell of the output lattice can be divided into two cells of the adapted lattice, and if the cell length is doubled, two cells of the output lattice are combined and combined to form a cell of the adapted lattice.

In a further preferred embodiment, the cells of the grid can be arranged in blocks and managed block by block. The blocks may each have an equal number of cells in n rows and m columns. Preferably, the number of rows n is equal to the number of columns m. More preferably, the cells of a block can each represent surrounding areas with the same geometry.

Particularly with a large number of cells, the block-wise arrangement and management of the cells makes the software-technical administration, in particular the storage, updating and also the transfer to downstream applications, which evaluate the information stored in the grid card, more efficient.

It is also possible that the blocks have different cell sizes depending on the distance from the vehicle. As a result, a distance-dependent resolution can be realized.

The method may further comprise a step of transmitting information of the lattice map to at least one downstream application, wherein the transmission is block by block, and wherein the blocks are transmitted in an order, first blocks near the vehicle, then more distant blocks in front of the vehicle, and finally blocks be transferred behind the vehicle. Alternatively, the blocks may be transmitted in an order whereby first, more distant blocks in front of the vehicle, then blocks near the vehicle and finally blocks behind the vehicle are transmitted.

The transmission of the information of the environment model can be adapted in this way so that it is advantageous from the point of view of the information-consuming, downstream application. Thus, a transmission in which information about the immediate vicinity of the vehicle is sent first allows a downstream application to respond quickly to changes in the immediate environment, such as initiating emergency braking, when an object suddenly crossing the lane of the vehicle is detected Conversely, for example, an early detection of a far ahead obstacle on the roadway allow to plan and execute a corresponding evasive response, so as to avoid, for example, an emergency stop or an accident.

For each block, more preferably, a flag may be stored indicating whether or not at least one cell of the block has been modified by new sensor measurements from the last update cycle.

With the help of the flag can be checked in a quick and easy way, if a block has been modified. If the flag indicates that there is no modification, downstream applications may be able to dispense with re-evaluation of the block or the cells combined in the block, and computing time can be saved.

As a further solution, an environment model unit is provided for providing an environment model for a vehicle, wherein the environment model unit is adapted to receive data from at least one sensor system for environment detection, and based on the received data to create a grid map as the environment model, wherein the grid Grid map consists of a plurality of cells, each representing an area of the environment of the vehicle; and wherein the environment model unit is further adapted to adjust the representation of the environment by the grid map depending on a driving situation of the vehicle by changing the size and / or geometry of the areas of the environment that are from the cells are represented, and / or by changing the arrangement of the cells in the grid of the grid card.

The environment modeling unit is preferably further configured to perform the methods described herein.

The environment model unit can be part of a driver assistance system.

As a further solution, a vehicle is specified, which has at least one sensor system for detecting the surroundings of the vehicle, and further comprises the environment model unit and / or the driver assistance system.

The present invention will be described below with reference to preferred embodiments, with reference to the drawings:

1 schematically shows a vehicle according to an embodiment;

2 schematically shows an exemplary grid for a grid map for a first driving situation;

3 schematically shows an exemplary driving situation of a vehicle that moves on a multi-lane roadway of a highway;

4 schematically shows an exemplary grid for a grid map for the driving situation of 3 ;

5 schematically shows another exemplary driving situation of a vehicle that moves on a multi-lane roadway of a highway;

6 schematically shows an exemplary grid for a grid map for the driving situation of 5 ; and

7A to 7C show exemplary grids for grid cards, which are composed of a plurality of blocks of cells.

In the 1 is a vehicle 1 illustrated according to an exemplary embodiment. The vehicle 1 is with a sensor system 10 equipped, which is arranged, at least an area of the environment of the vehicle 1 sensory. The sensor system 10 For example, a camera system may be an area in front of the vehicle 1 detected and which may, for example, be adapted to detect lane markings, vehicles in front or other objects on or next to the roadway. This example is not limiting, and it can be used as a sensor system 10 alternatively or additionally, other sensor systems, such as radar systems for near or far range, ultrasound systems or other known systems for detecting the environment of the vehicle 1 , or any combination thereof. Also, the environment detection is not on a detection of the area in front of the vehicle 1 limited, and it may alternatively or additionally also areas laterally and / or behind the vehicle 1 be detected, with particularly preferred 360 ° detection around the vehicle 1 can be realized.

The of the sensor system 10 detected sensor data, possibly after a preprocessing such as a plausibility, association and fusion of the outputs of several individual, different sensors of the sensor system 10 , to an environment model unit 20 output.

The environment model unit 20 is set up based on the received sensor data, to create an environment model in the form of a grid map, which is the environment of the vehicle 1 describes. The environment of the vehicle 1 is for this purpose divided into a grid or "grid" in a flat plane in a plurality of adjacent cells, each cell a corresponding area of the environment of the vehicle 1 represents. Based on the received sensor data, in each case corresponding information values are assigned to the cells of the grid, in order in such a way a grid map as a representation of the environment of the vehicle 1 to create. The information values assigned to the cells may be allocation information indicating whether the cell, or the area of the environment represented by the cell, has been identified as occupied or free to create a grid map in the form of an occupancy map. The occupancy information may be stored as binary information, that is, as 0 or 1, or preferably as probability values ranging between 0 and 1, to indicate the probability of occupancy. However, this is only an example, and the environment model unit 20 may also be arranged to create other types of occupancy maps, or other grid-based map types such as feature maps containing, for example, elevation information or intensity information.

The from the environment model unit 20 The grid map created can be output to various applications, in particular driver assistance function applications. In the 1 Here is, for example, a lane detection unit 50 which is based on that of the environment model unit 20 created and output grid map perform an object recognition for recognizing lane markings and based on it a recognition of the course of the lane of the vehicle 1 can perform. The information about the recognized lane may be from the lane recognition unit 50 again the environment model unit 20 be made available, for example to the environment model unit 20 to allow the representation of the environment by the grid map to adapt to the course of the lane.

Like in the 1 further illustrated, the vehicle can 1 continue an odometry unit 30 which may be configured, information about the position, orientation and speed of the vehicle 1 provide. Optionally, a navigation device 40 be provided, which can provide information on a road type, a lane width, the number of lanes or a lane course based on data of a digital road map. This information can be obtained from the environment model unit 30 be used to determine whether and, if appropriate, how an adjustment of the representation of the environment by the grid map should or can be performed.

With reference to the 2 to 7C will now be described in greater detail, such as the environment of the vehicle 1 can be represented by the grid map, as well as the possibilities to adapt the representation of the environment in a suitable manner to different driving situations.

The 2 shows a grid 2 with a variety of cells 3 , Each of the cells 3 represents a representation of a square area around the vehicle 1 dar. The cells 3 are arranged in regular rows and columns, with the number of cells 3 a row of the number of cells 3 in a column. This results in a square grid 2 that has a corresponding square area around the vehicle 1 represents. The cells 3 For example, each may represent a square area of the environment of 4 cm × 4 cm. The square grid 2 For example, it can be made up of 1,000 × 1,000 cells. It can be a square area of 40 m × 40 m in the environment of the vehicle 1 represented and represented in the form of a grid map as an environment model.

The grid map is world-fixed, that is, with a coordinate system that has a fixed relation to the real world, and the vehicle 1 moves relative to the grid map. cell 3 behind the vehicle 1 , due to the vehicle movement from the field of view of the vehicle 1 wander, be removed and as new cells 3 at corresponding opposite locations of the grid 2 newly inserted. This can be done in rows or columns. It can also be provided that this for each individual cells 3 respectively. In this way, the grid map 2 with the movement of the vehicle 1 "Co-migrate".

The example of 2 provides a relatively high-resolution environmental model, starting from the essentially centered vehicle 1 the environment up to an approximately equal distance in each direction from the vehicle 1 maps. This type of environment representation can be particularly suitable for parking situations or in complex urban driving situations, in which a highly accurate localization of other objects in the immediate vicinity of the vehicle 1 is desirable.

The 3 exemplifies a driving situation in which the vehicle 1 on a three-lane road 8th a highway moves. The individual lanes of the roadway 8th are by lane markings 6 marked. The lines 7 represent lane boundaries.

The driving situation of driving on a highway is often in Germany especially at high speeds of both the own vehicle 1 , as well as other vehicles associated, the speeds can exceed a value of, for example, more than 200 km / h. In this situation, it is therefore desirable, in particular for future developments in the field of highly autonomous driving, to detect the traffic ahead of the vehicle with a distance of vision of greater distances of 80 m, 100 m or more and to map it in the environmental model.

Would that be in relation to the 2 illustrated and described principle of a high-resolution, square grating 2 according to the driving situation of the 3 applied, the number of cells would have to be multiplied by the square of the corresponding magnification factor for an enlarged look-ahead range.

To avoid this, it is therefore proposed to represent the environment of the vehicle 1 to adapt by the grid map to the changed driving situation, as exemplified in the 4 shown.

Like in the 4 can be shown for the driving situation of the 4 a grid 2 used, which is not square, but essentially along the roadway 8th , or a lane 5 , especially the lane 5 of the vehicle 1 , is constructed. In particular, as in the 4 shown the grid 2 as a rectangular grid 2 be configured with the grid 2 essentially along the course of the lane 5 is aligned so that the longitudinal edges of the cells 3 essentially parallel to the course of the lane 5 are.

The information about the course of the lane 5 can, for example, from the navigation device 40 be provided, or may be from the lane detection unit 50 to be appreciated. In the event that the information about the course of the lane 5 falls away, for example, because the navigation device 40 does not contain any map data over a traveled area, or because on a traveled route the lane markings 6 due to wear so bad or can not be detected that the lane detection unit 50 can not detect the lane course, so a last current lane course can be maintained and extrapolated into the future. Alternatively, starting from the last current lane course, the curvature can be gradually reduced to zero. If indicated by circumstances, the look-ahead range can be adjusted accordingly.

In the longitudinal direction of the lane 5 the resolution of the grid map can be reduced. Accordingly, the cells can 3 , or from each cell 3 represented area of the environment, also be formed rectangular, so that the cells 3 each represent an area that is longer than it is wide. The cells 3 For example, each may represent an area of 16 cm in length. That way, without the number of cells 3 of the grid 2 increase in the longitudinal direction, the foresight range can be significantly extended. Will the length of the cells 3 for example, depending on the speed of the vehicle 1 adapted, the look-ahead range of the speed can be adjusted.

Because the vehicle 1 essentially parallel to the longitudinal direction of the grid 2 , and thus parallel to the longitudinal direction of the cells 3 Moving is caused by the change in length of the cells 3 the resolution in the lateral direction is not significantly affected. Such a resolution has been shown in practical experiments as sufficiently accurate for many current and future intended applications in particular for highway driving at high speed.

Side of the vehicle 1 it may be enough that the grid 2 cover only the area of the roadway up to the first lateral obstacles. These are usually the road edges, which may be marked for example by crash barriers, guide posts, curbs, a sod, and so on. This may be the case, in particular, if that of the environment model unit 20 provided environment model only to applications 50 . 60 is provided, which has no information about events off the road 8th need. For other applications, it may also make sense that the grid 2 covers only the area of a driving tube in which the vehicle is moving.

For other applications, such as a Simultaneous Localization and Mapping (SLAM) application, it may additionally be necessary to go beyond the obstacles on either side of the roadway 8th to detect an additional area, such as an additional 3 m or 5 m wide strip beyond the first lateral obstacles, for example to be able to image buildings or other landmarks that can serve for localization in the grid map.

In both cases, it is therefore sufficient to the side of the vehicle 1 To capture and map a relatively limited width in the environment model, such as 20 m, 30 m, or 40 m. This allows it for the cells 3 a high resolution in the direction transverse to the course of the roadway 8th to choose, for example, 4 cm.

The limitation of the grid map in the lateral direction may further have the advantage of the quality of the representation of the environment of the vehicle 1 through the grid map to improve. This is due to the fact that in the area of the lateral limits of the detection range of the sensor system 10 During the journey, a sufficient number of measurement results can often not be obtained in order to be able to derive reliable values for the grid map.

To the above-described adaptation of the grid 2 by changing the length and / or the width of the cells 3 or the cells 3 represented areas of the environment of the vehicle 1 can make the environment model unit 20 for example, starting from a current grid map with a first grid configuration calculate a new grid map with a correspondingly changed and adapted second grid configuration. For this purpose, the second grid 2 superimposed on the current grid map and based on the information of the current grid map the corresponding values for the new grid map are calculated. In this way, it is possible to switch from the current grid map to the new grid map in one update cycle.

Alternatively, the adjustment can also be made successively, for example, such that behind the vehicle 1 out of sight cells 3 the current grid map will be removed and in the field of vision in front of the vehicle 1 new cells 3 with correspondingly changed geometry according to the adapted second grid configuration.

In both cases, it is preferred that changes in the length and / or width of the cells 3 be made only in discrete steps in order to avoid or reduce the amount of computation time required for this conversion, as well as by the conversions possibly caused errors. It is particularly preferred if as discrete steps only respective doubling and halving the length and / or the width of the cells 3 be made, for example, from 4 cm to 8 cm to 16 cm to 32 cm in length or width. For example, when the cell length is doubled, for example, two cells adjoining each other in the longitudinal direction can be used 3 to a new cell 3 summarized, and at a halving the cell length, the cells 3 in each case two new cells 3 be split.

It is further preferred that angle changes, in particular as a rotation of the orientation or the longitudinal axis of the grid 2 , also be made only in discrete steps. An angle change can be carried out such that between at least two rows of the grid 2 an angular offset around a full cell 3 is achieved. For example, with a 1: 1 length to width ratio of a cell, this may correspond to an angle of 45 °, an angle of 22.5 ° to a 2: 1 ratio and an angle of 11 to a 4: 1 ratio, 23 °. This can be realized by shifting the contents of the cells to the right or left line by line in accordance with the change of the curvature.

Furthermore, it can also be provided that in the environment model unit 20 two grid maps are calculated, each with different grid configurations. For example, a square, high-resolution grid map parallel to a long, to the lane 5 adjusted grid map. In this case, it is not necessary to "switch" between different grid configurations and convert, thereby precluding the conversion as a possible source of errors. This may be advantageous in particular for applications of highly autonomous driving, in which the advantages of the improvement in reliability and reliability that can be achieved thereby outweigh the increase in storage and computing time required due to the parallel provision of two different grid maps.

While in the 4 the grid 2 is shown as rectangular, this is not limiting, and it is also possible that the cells 3 each represent areas of another, non-rectangular geometry, such as in the 5 and 6 shown.

The 5 exemplifies a section of a three-lane roadway 8th a highway in the area of a curve. In this case, as in the 6 represented the geometry of the cells 3 , or the geometry of the cells 3 Represented areas of the environment, be chosen so that they are bounded in the longitudinal direction of each of two parallel, extending in the longitudinal direction curves, wherein the curves are substantially parallel to the course of the lane 5 , This results in a grid map that is very accurate to the course of the road 8th follows, with the added benefit of having the vehicle 1 in its movement along the lane course 5 always parallel to the longitudinal direction of the curved grid 2 emotional. It thereby becomes the necessity for recalculations or conversions of the grid map 2 because of a changed orientation of the vehicle 1 significantly reduced relative to the grid map.

Instead of the cells bounded by the curves 3 as they are in the 6 can also be represented cells 3 used in the form of trapezoids to track the lane 5 approach in sections.

In the examples of 4 and 6 were the lattices 2 each as a grid 2 with a number of cells that are the same in the rows and columns 3 shown. However, this is not limiting, and it is also possible, for example, the number of cells 3 in the direction transverse to the course of the lane 5 each to be adapted to the width to be represented. For example, the number of cells 5 in the width direction, as the number of lanes increases, or in areas of ascents or descents of the lane 8th , or it may be the number of cells 3 be reduced in the width direction when a lane is omitted. In addition, it may also be possible to determine the number of cells 3 in the longitudinal direction of the lane course 5 thereby reducing or increasing accordingly, to a total grid 2 with a constant number of cells 3 to obtain.

The number of cells 3 in the length and / or width of the grid 2 can also be varied to address situations where there are several possible driving tubes for the movement of the vehicle 1 There are, for example, when merging or sharing the highway, or another type of road, such as at junctions, driveways or departures. In particular, it can be provided in this case, for each possible route a customized grid 2 provided.

In this way, by adjusting the size of the areas of the environment, that of the cells 3 be represented, and / or by changing the arrangement of the cells 3 in the grid 2 of the Grid map, which is adapted by the grid map as an environment model area adapted to a particular driving situation, without the need for the number of cells 3 increased or substantially increased.

Another simplification of the management and handling of the cells 3 of the grid 2 can be achieved when the cells 3 in groups of blocks B are summarized and managed together, as in the 7A to 7C shown.

The 7A to 7C show different configurations of grids 2 , which are each formed by a plurality of blocks B1 to B10, collectively designated B. Each block B in turn comprises a plurality of cells 3 , Preferably, the blocks B may each have n rows and m columns of cells in the manner of a matrix, where n and m are integers. The cells 3 of a block B preferably each have a same geometry, that is, they each describe a portion of the environment of the vehicle 1 of the same geometry.

Each block B has a world-wide position. Blocks B falling from the area of the environment to be covered are deleted and reinserted at a position of the environment to be newly covered. Depending on the direction, direction change and / or speed of the vehicle 1 , and / or width of the carriageway 8th The blocks B are thereby not only at the rear boundary of the field of view, but also removed laterally and newly set laterally or at the front boundary of the field of view. If, for example, the 7A to 7C As viewed as a series of lattice configurations occurring at different times in the course of a rotation of the vehicle 90 degrees to the left, for example, blocks B are removed in the course of the rotation from the right edge of the field of view and added to the left edge of the field of view. As in particular in the 7B represented, the blocks B can be arranged offset relative to each other, for example, offset by one, two or more cell rows or columns.

In order to realize a distance-dependent resolution, blocks B with different cell sizes can be further used for different distances, with further blocks B having a coarser resolution. In the example blocks B1 to B4 could have a resolution of 16 cm, while blocks B5 to B10 could each have a resolution of 8 cm.

It is preferably provided that the blocks B are arranged such that they track the course of the lane 5 approach as well as possible. In particular, it can be provided that the blocks B are arranged so that the best possible coverage of the road course 5 or the driving tube. For example, it can be achieved that the largest possible area for driving the vehicle 1 relevant environment is mapped by the lattice map formed from the corresponding blocks B, while other areas of the environment, such as areas of the first lateral obstacles that are not or only of minor relevance, not or only to a small extent are mapped.

The arrangement of the cells 3 in blocks B can also be advantageously exploited to a grid map as an environment model to downstream applications 50 . 60 transferred to. For example, the transmission order of blocks B can be adjusted to suit the application 50 . 60 is advantageous. For example, the closest to the vehicle could be first 1 lying blocks B5 to B8, then the removed blocks B1 to B4, and finally the behind the vehicle blocks B9, B10 are transmitted.

Depending on the application, it may also be beneficial to transfer more distant data earlier in the cycle so that the applications 50 . 60 be able to adapt to a driving situation that is very far ahead, although it can be assumed that it is close to the vehicle 1 Only a few changes occur or can not be reacted to. This could be achieved, for example, by the transmission order B5, B6, B1, B2, B3, B4, B7, B8, B9, B10.

In both cases, it may further be preferable for information to be transmitted for each block B on the position and orientation of the block B in the world-wide coordinate system, as well as, if appropriate, additional information about the number and / or arrangement of the cells 3 within the block B and / or over the size and geometry of the cells 3 of the block B. This way it allows the applications 50 . 60 be facilitated to evaluate the corresponding information of the block B already directly after receipt, without waiting for the transmission of the full grid card information.

In block-wise representation, it can also be advantageous to store a flag for each block B, which indicates a modification by new sensor measurements in relation to the last cycle. If a block B has not been modified, that is, none of the cells 3 The block has undergone a change, for example, to a merger into a central grid map or a re-evaluation by an application 50 . 60 dispensed with and thus computing time can be saved.

As described above, the environment model unit 20 , by a suitable choice of cell size, cell geometry and grid configuration, a representation of the environment of the vehicle adapted to the respective driving situation 1 through a grid map. It is also possible in particular that the environment model unit 20 with a given number of cells 3 , or a predetermined upper limit for the number of cells 3 in the grid 2 , can work to realize the various possible and desirable environmental model representations, in particular, different desirable predictive ranges. Accordingly, the amount of computing time, as well as the requirement of required memory, which is required to store the information of the grid card, be limited.

In order to determine which form of representation of the environment by a grid map is most suitable for a current driving situation, it can be provided that the environment model unit 20 is arranged to solve an optimization problem in which the cell sizes, cell geometry and grid configuration are considered as input parameters in order to maximize an objective function, for example to maximize the relevance and resolution weighted imaged area of the environment.

Alternatively, it may also be possible that suitable forms of representation of the environment are given for different typical driving situations and the environment model unit 20 based on a recognized driving situation selects and applies the appropriate form of representation. For example, for a parking operation, driving in urban traffic, over-country driving and driving on highways respectively, specifications can be made about the grid configuration to be used, cell size, cell geometry and so on. Alternatively or additionally, specifications can also be provided depending on speeds, such as, for example, according to whether the vehicle 1 Moving at less than 10 km / h, between 10 km / h and 60 km / h, between 60 and 120 km / h or over 120 km / h.

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Cited patent literature

• DE 102007013023 A1 [0003]
• DE 102009007395 A1 [0003]
• DE 102010006828 A1 [0003]
• DE 102011081740 A1 [0003]
• WO 2013/060323 A1 [0003]

Claims (15)

Method for providing an environment model for a vehicle ( 1 ), comprising the steps of: receiving data from at least one sensor system ( 10 ) for environment detection; Creating a grid map, as the environment model, based on the received data, where the grid ( 2 ) the grid map of a plurality of cells ( 3 ), each covering an area of the surroundings of the vehicle ( 1 represent); and adapting the representation of the environment by the grid map depending on a driving situation of the vehicle ( 1 ) by changing the size and / or geometry of the areas of the environment that the cells ( 3 ) and / or by changing the arrangement of the cells ( 3 ) in the grid ( 2 ) of the grid map. The method of claim 1, wherein the driving situation comprises at least one of a speed of the vehicle ( 1 ), a road type, a traffic density, a lane course, and a lane width. The method of claim 2, wherein the grid map substantially along the course of the lane of the vehicle ( 1 ) is constructed. Method according to claim 3, wherein the cells ( 3 ) at least one row of the grid ( 2 ) represent a region which is bounded on two opposite sides by a curve which substantially corresponds to the course of the traffic lane. Method according to one of the preceding claims, wherein the cells ( 3 ) at least one row of the grid ( 2 ) represent an area whose extension is adapted in the direction of the vehicle movement depending on the speed of the vehicle ( 1 ). Method according to one of the preceding claims, wherein the cells ( 3 ) at least one row of the grid ( 2 ) represent an area whose extension in the direction of vehicle movement is an integer multiple of the extension in the direction transverse to the vehicle movement. Method according to one of the preceding claims, wherein the adjustment is made in discrete steps, preferably in steps of doubling or halving extents. Method according to one of the preceding claims, wherein the cells ( 3 ) of the grid ( 2 ) are arranged in blocks (B), wherein the blocks (B) each have an equal number of cells (B) 3 ) in n rows and m columns, where n and m are preferably the same, and more preferably all cells ( 3 ) of a block (B) represent regions of identical geometry. Method according to claim 8, wherein depending on the distance from the vehicle ( 1 ) the blocks (B) have different cell sizes. The method of claim 8 or 9, further comprising a step of transmitting the information of the grid map to at least one downstream application ( 50 . 60 ), wherein the transmission is block by block, and wherein preferably the blocks (B) are transmitted in an order whereby first blocks (B5 to B8) close to the vehicle ( 1 ), then more distant blocks (B1 to B4) in front of the vehicle ( 1 ) and finally blocks (B9 to B10) behind the vehicle ( 1 ), or wherein first more distant blocks (B1 to B4) in front of the vehicle ( 1 ), then blocks (B5 to B8) near the vehicle ( 1 ) and finally blocks (B9 to B10) behind the vehicle ( 1 ) be transmitted. Method according to one of the preceding claims, wherein a flag is further stored for each block (B), which indicates whether at least one cell (due to new sensor measurements in relation to the last update cycle) ( 3 ) of the block (B) has been modified or not. Environment Model Unit ( 20 ) for providing an environment model for a vehicle ( 1 ), wherein the environment model unit ( 20 ) is arranged to receive data from at least one sensor system ( 10 ) for environment detection, and based on the received data to create a grid map as the environment model, wherein the grid ( 2 ) the grid map of a plurality of cells ( 3 ), each covering an area of the surroundings of the vehicle ( 1 represent); and wherein the environment model unit ( 20 ) is further adapted to adapt the representation of the environment by the grid map depending on a driving situation of the vehicle ( 1 ) by changing the size and / or geometry of the areas of the environment that the cells ( 3 ) and / or by changing the arrangement of the cells ( 3 ) in the grid ( 2 ) of the grid map. Environment Model Unit ( 20 ) according to claim 12, wherein the environment model unit ( 20 ) is arranged to carry out the method according to one of claims 1 to 11. Driver assistance system, comprising an environment model unit ( 20 ) according to any one of claims 12 to 13. Vehicle ( 1 ), comprising at least one sensor system ( 10 ) for detecting the environment of the vehicle ( 1 ); and an environment model unit ( 20 ) according to claim 12 or 13, and / or a driver assistance system according to claim 14.

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