METHOD AND DEVICE FOR OPERATING AN ASSISTANCE SYSTEM OF A VEHICLE, AND A VEHICLE

Abstract

A method and a device for operating an assistance system of a vehicle involves detecting laterally static and laterally dynamic objects, which the vehicle is to drive past, as lateral boundary objects. A respective lateral distance of the vehicle from the respective lateral boundary object is detected. A speed of the respective laterally dynamic object is determined and at least the respectively laterally dynamic object is classified according to its type. A set of characteristic curves is stored in a control unit of the vehicle, the characteristic curves of the set being assigned in each case to an environmental situation predetermined depending on lateral boundary objects. It is predetermined by a respective characteristic curve for the respective environmental situation at what maximum speed the vehicle is to drive past a lateral boundary object at different lateral distances from the latter.

Claims

1-10. (canceled)

11. A method for operating an assistance system of a vehicle, the method comprising: detecting, laterally static and laterally dynamic objects, which the vehicle is to drive past, as lateral boundary objects; detecting a respective lateral distance of the vehicle from each detected lateral boundary objects; determining a speed of the detected lateral boundary objects; classifying, at least the detected laterally dynamic objects, according to a type of laterally dynamic object; and controlling the vehicle based on a characteristic curve selected from a set of characteristic curves stored in a control unit of the vehicle, wherein each characteristic curve of the set of characteristic curves is assigned to an environmental situation predetermined depending on detected lateral boundary objects, and wherein each characteristic curve of the set of characteristic curves predetermines a maximum speed the vehicle is to drive past the detected boundary object at different lateral distances from the detected boundary object.

12. The method of claim 11, wherein characteristic curves of the set of characteristic curves for a current environmental situation on a left lane side and on a right lane side of the vehicle are selected, and a maximum speed and a lateral target position of the vehicle between two lateral boundary objects is controlled based on the selected characteristic curves.

13. The method of claim 11, wherein the maximum speed varies depending on the detected lateral boundary object.

14. The method of claim 12, wherein the selected characteristic curves corresponding to the environmental situation on the left and right lane sides is converted into a recommended maximum speed based on a movement speed of the respective lateral boundary object.

15. The method of claim 12, wherein the selected characteristic curves corresponding to the environmental situation on the left and right lane sides are added to form an overall characteristic curve that is used to control the vehicle.

16. The method of claim 11, wherein the determination of the maximum speed comprises determining a free width remaining between a lateral boundary object on the left lane side and the vehicle and between a lateral boundary object on the right lane side of the vehicle.

17. The method of claim 11, wherein the laterally dynamic objects include further vehicles, pedestrians, motorcyclists, and cyclists.

18. The method of claim 11, wherein the laterally static objects include lane markings, crash barriers, tunnel walls, and bridge pillars.

19. A device for a vehicle, comprising: an environmental sensor system configured to detect laterally static and laterally dynamic objects that the vehicle is to drive past, as lateral boundary objects, detect a respective lateral distance of the vehicle from each detected lateral boundary objects, and determine a speed of the detected lateral boundary objects, wherein at least the detected laterally dynamic objects are classified according to a type of laterally dynamic object; an assistance system configured to control the vehicle based on a characteristic curve selected from a set of characteristic curves stored in a control unit of the vehicle; and a control unit that stores the set of characteristic curves, wherein each characteristic curve of the set of characteristic curves is assigned to an environmental situation predetermined depending on detected lateral boundary objects, and wherein each characteristic curve of the set of characteristic curves predetermines a maximum speed the vehicle is to drive past the detected boundary object at different lateral distances from the detected boundary object.

Description

BRIEF DESCRIPTION OF THE DRAWING FIGURES

[0023] Here are shown:

[0024] FIG. 1 schematically, a coordinate system having a set of characteristic curves,

[0025] FIG. 2 schematically, two characteristic curves and an overall characteristic curve,

[0026] FIG. 3 schematically, a vehicle, a free usable width for the vehicle and a further vehicle on a section of road,

[0027] FIG. 4 schematically, a coordinate system having a maximum speed determined by means of the overall characteristic curve,

[0028] FIG. 5 schematically, a coordinate system for determining a left target distance,

[0029] FIG. 6 schematically, a coordinate system for determining a right target distance and

[0030] FIG. 7 schematically, the section of road according to FIG. 3 and the two coordinate systems according to FIGS. 5 and 6.

[0031] Parts corresponding to one another are provided with the same reference numerals in all figures.

DETAILED DESCRIPTION

[0032] FIG. 1 shows a coordinate system K having a so-called characteristic curve set consisting of five characteristic curves K1 to K5.

[0033] Each of the characteristic curves K1 to K5 represents an environmental situation for a vehicle 1 depicted in more detail in FIG. 3 on a road section F.

[0034] In particular in the highly automated driving mode of the vehicle 1, it is necessary to determine a target speed vm of the vehicle 1, hereinafter referred to as maximum speed vm, and a lateral target position, a so-called transverse position, of the vehicle 1, depending on or alongside a lane F1 of the vehicle 1 shown in FIG. 3.

[0035] To determine the maximum speed vm and the lateral target position for the vehicle 1, a method described below is provided.

[0036] For this purpose, the environmental situation of the vehicle 1 is detected, in particular by means of detection units of an environmental sensor system of the vehicle 1, by means of a vehicle-to-infrastructure communication, and/or by means of other suitable means and information.

[0037] The environmental situation is determined by static objects and/or dynamic objects as lateral boundary objects B, wherein boundary objects B are depicted by way of example in FIG. 3.

[0038] Crash barriers, tunnel walls, bridge pillars, lane markings M depicted in FIG. 3 are, inter alia, detected as static objects, wherein a further vehicle 2 shown in FIG. 3, pedestrians, cyclists are, inter alia, detected as dynamic objects.

[0039] In the vehicle 1, the set of characteristic curves is stored and predetermined in a control unit, wherein each characteristic curve K1 to K5 is assigned to an environmental situation, i.e., represents an environmental situation. By way of example, the control unit is a component of an assistance system for highly automated, i.e., autonomous, driving operation of the vehicle 1.

[0040] A respective characteristic curve K1 to K5 predetermines a recommended maximum speed vm and a lateral distance ds between the vehicle 1 and the detected static object and/or dynamic object determining the environmental situation, i.e., to the lateral boundary object B, for the respective environmental situation.

[0041] According to the coordinate system K in FIG. 1, the maximum speed vm is plotted on the ordinate and the lateral distance ds on the abscissa.

[0042] The maximum speed vm, which serves as a recommendation for driving past the detected lateral boundary object B, depends on the lateral distance ds, and represents a driving speed for the vehicle 1 at which the vehicle 1 is to drive past the respective lateral boundary object B at different possible lateral distances ds, in particular in the highly automated driving mode.

[0043] Moreover, the maximum speed vm represents an absolute or even relative driving speed of the vehicle 1 depending on the detected environmental situation and depending on whether the detected lateral boundary object B is a static object or a dynamic object.

[0044] In the case of a dynamic object as a lateral boundary object B, it is advantageous to initially predetermine the corresponding characteristic curve K1 to K5 in such a way that it represents a relative maximum speed vm related to the respective dynamic object. These characteristic curves K1 to K5 are then converted into the recommended absolute maximum speed vm based on a current speed of the detected dynamic object, in the following also called speed of movement.

[0045] To determine the maximum speed vm and the lateral target position of the vehicle 1, which is also dependent on the lateral distances ds, a characteristic curve K1 to K5 corresponding to the detected environmental situation is selected for both a left lane side and a right lane side.

[0046] By way of example, a first characteristic curve K1 is selected if a crash barrier is located next to the lane F1 of the vehicle 1 as a static object and thus as a lateral boundary object B.

[0047] A second characteristic curve K2 is selected, for example, if another vehicle 2 is located next to the lane F1 of the vehicle 1 as a lateral boundary object B.

[0048] If a pedestrian or a (motor)cyclist is located next to the lane F1 of the vehicle 1 as a lateral boundary object B, a third characteristic curve K3 is selected and used as the basis for a control of the vehicle 1.

[0049] A fourth characteristic curve K4 is then selected if the lane F1 of the vehicle 1 is an outer one whose lateral area, for example a hard shoulder S shown in FIG. 3, can be driven on. In such a case, the lane marking M represents the static object, i.e., the lateral boundary object B. The lateral distance ds refers to a lateral distance between the vehicle 1 and the lane marking M, wherein a negative lateral distance ds indicates that an area outside the lane F1 can or is allowed to be driven on.

[0050] In the case that there is a free lane F2 next to the lane F1 of the vehicle 1, the lane marking M also represents a static object as a lateral boundary object B and a fifth characteristic curve K5 is selected.

[0051] From the set of characteristic curves, the fifth characteristic curve K5 corresponding to the detected environmental situation is then selected for the left side of the lane and the second characteristic curve K2 corresponding to the environmental situation is selected for the right side of the lane, in accordance with the exemplary embodiment in FIG. 3.

[0052] The fifth characteristic curve K5 and the second characteristic curve K2 are then added in the direction of the ordinate to form a total characteristic curve K6, as shown in FIG. 2. For a possible combination, this can be determined in advance on the vehicle side at absolute movement speeds.

[0053] Subsequently, a remaining width b, i.e., a distance between the detected lateral boundary object B on the left lane side, namely the lane marking M, and the detected lateral boundary object B on the right lane side, namely the further vehicle 2, is determined at the height of the respective lateral boundary object B. From the remaining width b, a free usable width bn depicted in FIG. 4 is determined, which is determined using the remaining width b minus a vehicle width bf shown in FIG. 7.

[0054] By means of the free usable width bn, the maximum speed vm can then be determined from the overall characteristic curve K6, as shown in FIG. 4.

[0055] Using the determined maximum speed vm, a lateral target distance ds_l shown in FIG. 5 in the direction of the left side of the lane and a lateral target distance ds_r in the direction of the right side of the lane shown in FIG. 6 can then be determined from the two selected characteristic curves K5, K2.

[0056] The two lateral target distances ds_l, ds_r generally do not lead to a central positioning of the vehicle 1 between the detected lateral boundary objects B, i.e., the free usable width bn.

[0057] An actual lateral target position P of the vehicle 1 shown in FIG. 7 can be predetermined by means of a distance of the vehicle 1 starting from its center to the center of the lane FM or as a distance to another reference line, e.g., to the lane marking M of the lane F1 of the vehicle 1.

[0058] FIG. 7 shows an overview of the application of the method with the road section F according to FIG. 3 and the two coordinate systems K according to FIGS. 5 and 6.

[0059] In a possible embodiment of the method, it is provided that objects alongside the lane F1 are classified, wherein a respective characteristic curve K1 to K5 is predetermined for each object class, for example passenger cars, lorries.

[0060] Furthermore, it is conceivable to predetermine different characteristic curves K1 to K5 for different operating states of the vehicle 1. By way of example, for a vehicle 1, which comprises an assistance system for automated driving, a distinction can be made between automated driving and manual driving.

[0061] Alternatively, or additionally, it can be provided that a parameterization of the characteristic curves K1 to K5 is carried out depending on a prevailing general traffic situation, e.g., congestion/free-flowing traffic, motorway/urban motorway/country road/other road, wherein a characteristic curve K1 to K5 is predetermined for each of these traffic situations.

[0062] Although the invention has been illustrated and described in detail by way of preferred embodiments, the invention is not limited by the examples disclosed, and other variations can be derived from these by the person skilled in the art without leaving the scope of the invention. It is therefore clear that there is a plurality of possible variations. It is also clear that embodiments stated by way of example are only really examples that are not to be seen as limiting the scope, application possibilities or configuration of the invention in any way. In fact, the preceding description and the description of the figures enable the person skilled in the art to implement the exemplary embodiments in concrete manner, wherein, with the knowledge of the disclosed inventive concept, the person skilled in the art is able to undertake various changes, for example, with regard to the functioning or arrangement of individual elements stated in an exemplary embodiment without leaving the scope of the invention, which is defined by the claims and their legal equivalents, such as further explanations in the description.