Method and device for setting operating state of driver assistance system

Abstract

The invention relates to a method for adjusting the operating state of a driving assistance system which is designed to control the lateral guidance of a motor vehicle (1) on the basis of image data recorded by means of a camera (2) of the motor vehicle (1). The method comprises determining (S1) a weather condition in the environment of the motor vehicle (1) on the basis of the image data, identifying (S2) a lane marking (4) on the basis of the image data, determining (S4) a length (L) of the identified lane marking (4), and adjusting (S5) an operating state of the driving assistance system on the basis of the determined weather condition and the determined length (L) of the identified lane marking (4).

Description

Technical Field

[0001] The present disclosure relates to a method for adjusting the operating state of a driver assistance system, which is configured to control the lateral guidance of a motor vehicle based on image data recorded by a camera of the motor vehicle. Additionally or alternatively, a data processing device is provided, which is configured to at least partially execute the method. Additionally or alternatively, a motor vehicle is provided that at least partially includes a data processing device. Additionally or alternatively, a computer program including instructions is provided, which when the program is executed by a computer causes the computer to at least partially execute the method. Additionally or alternatively, a computer-readable medium including instructions is provided, which when the instructions are executed by a computer causes the computer to at least partially execute the method. Background Art

[0002] Current lateral guidance systems are primarily based on lane information recorded from sensor data of a front camera of the motor vehicle.

[0003] In this context, DE 41 24 654 A1 describes a method for continuous and automatic vehicle orientation on a roadway, comprising an image generation system and a computerized image analysis and evaluation device for generating vehicle control data, wherein the image data of the last monocularly generated image of a continuous image sequence are modeled with the aid of a program of a control electronic computer according to spatial geometric and temporal dynamic aspects of the scene, so that these can then be taken into account with the aid of a recursive estimation method for determining road parameters, in particular the horizontal and vertical curvature profile in a preview area as well as the width and conditions related to the road itself.

[0004] However, in bad weather (such as fog, low sunlight, snow, rain, etc.), the recognition quality of the front camera may sometimes be significantly reduced.

[0005] In order to prevent errors in the lateral guidance, attempts are therefore made to detect bad weather and to switch off the lateral guidance system as early as possible. This is necessary primarily in so-called hands-free systems (in which the driver does not have to keep his hands on the steering wheel at least permanently), because the requirements for lateral guidance performance are many times higher there than in so-called manual systems (in which the driver keeps his hands on the steering wheel at least permanently).

[0006] In this case, bad weather is detected in two ways by means of the same front camera, whose data are also used as input variables for the lateral guidance. On the one hand, bad weather is detected from the image data itself; on the other hand, bad weather is detected from the effective length of the detected lane markings, which can be used as input data for the lateral guidance.

[0007] Current systems use only one of the above identification methods, each of which has its drawbacks.

[0008] Identifying bad weather from the image data itself may result in identifying bad weather conditions too early or too late, as identification requires a certain amount of time. In addition, erroneous identification may occur due to erroneous image data / erroneous image interpretation.

[0009] Detecting bad weather from the effective length of the detected lane markings may have the disadvantage that even in good weather, the effective length may be limited because the lane markings are less visible. In these cases, erroneous deactivation of the function may occur. Summary of the invention

[0010] Against the background of this prior art, the object of the present disclosure is to specify a device and a method which are respectively suitable for at least enriching the above-mentioned prior art.

[0011] This object is achieved by the features of the independent claim. The dependent claims contain preferred developments of the invention.

[0012] The object is then achieved by a method for setting an operating state of a driver assistance system which is designed to control a lateral guidance of a motor vehicle based on image data recorded by means of a camera of the motor vehicle.

[0013] The method may be a computer-implemented method, ie one, several or all steps of the method may be executed by means of a computer or a data processing device.

[0014] A driver assistance system is an automated driving function, which may be understood as a function of a motor vehicle which is designed to take over parts of the driving task or the entire driving task at least temporarily, if necessary together with other automated driving functions.

[0015] A driver assistance system is a system having hardware and / or software components which receive image data and / or information generated on the basis of image data as input data, process the input data in a predetermined manner and thereby generate control signals in order to control the lateral guidance, which control signals are sent to the driver assistance system.

[0016] Depending on the degree of automation of the motor vehicle, the control of the lateral guidance can include active and / or passive intervention in the lateral guidance of the motor vehicle by means of a driver assistance system. The motor vehicle can also be configured to control the longitudinal guidance of the motor vehicle by means of the driver assistance system and / or a further driver assistance system. This can also be done based on image data.

[0017] The method includes determining weather conditions in an environment of the motor vehicle based on the image data.

[0018] Weather conditions can be understood as weather and / or optionally weather changes, predetermined dimensions of the motor vehicle in the environment or surroundings. Examples of weather conditions include brightness (e.g. due to the sun and / or oncoming vehicles, etc.) and / or precipitation (e.g. rain, snow and / or fog, etc.).

[0019] The method includes identifying a lane marking based on the image data and determining a length of the identified lane marking.

[0020] Lane markings can also be referred to as lane markings. This usually involves a color marking (e.g. white or yellow) on the surface of the traffic surface of the road where the road traffic, i.e. the motor vehicle, is located at the time of executing the method. Currently, so-called longitudinal markings are particularly suitable. The longitudinal markings are arranged longitudinally or along the direction of travel. The longitudinal markings largely serve as visual guidance for traffic participants.

[0021] Object recognition algorithms can be used to recognize lane markings.

[0022] The method includes adjusting an operating state of a driver assistance system based on determined weather conditions and a determined length of a recognized lane marking.

[0023] Setting the operating state may also be referred to as controlling the operating state and may include the output of control signals to a driver assistance system.

[0024] Possible embodiments of the method are described in detail below.

[0025] The setting of the operating state of the driver assistance system may include deactivating or preventing activation of the driver assistance system. In other words, depending on whether the driver assistance system is active at the time of setting the operating state determined based on the image data, the driver assistance system may be activated or remain active, or the driver assistance system may be deactivated or cannot be activated. Activation here means that the driver assistance system controls lateral guidance. Conversely, deactivation means that the driver assistance system does not control lateral guidance.

[0026] If the determined length of the recognized lane marking is below a predetermined threshold and the determined weather conditions meet predetermined criteria for severe weather conditions (eg precipitation exceeds a predetermined limit value), activation of the driver assistance system may be deactivated or prevented.

[0027] The method may include controlling a lateral guidance of the motor vehicle by means of a driver assistance system as a function of the set operating state of the driver assistance system based on the image data.

[0028] The lateral guidance of the motor vehicle can be controlled based on the course of the detected lane markings. Interventions in the lateral guidance can be made so that the motor vehicle follows a trajectory that runs essentially parallel to the lane markings. A trajectory can be understood as the path along which the motor vehicle is to travel (the so-called target trajectory) or the path actually traveled (the so-called actual trajectory). In addition to the position information, the trajectory can also have a time component, i.e. when the motor vehicle is to be where.

[0029] The determination of the weather conditions and / or the recognition and / or determination of the length of the lane markings can be performed by a camera. That is, the camera itself cannot output image data, for example, but rather the type or category of the weather conditions (e.g. "bad weather"), the course of the lane markings and / or the course of the lane center determined on this basis, and / or the length of the course of the lane markings. These can then be used as input data for the method. However, it is also conceivable that the camera itself performs the entire method in addition or alternatively.

[0030] The contents described above can be summarized in other words and as described below into possible specific configurations of the present disclosure, wherein the following description should not be interpreted as limiting the present disclosure.

[0031] The two recognition principles described in the introduction can be combined so that bad weather is detected from the image data itself and from the effective lengths of the detected lane markings (which can be used as input data for lateral guidance).

[0032] When the above two conditions are met at the same time, severe weather can be identified.

[0033] If bad weather is detected by this method, the lateral guidance system can be switched off.

[0034] This results in a more reliable detection of bad weather and leads to fewer unauthorized deactivations of the lateral control function.

[0035] In addition, a device for data processing is provided, which includes a device for executing the above method. The device for data processing can also be called a data processing system or a data processing device. More specifically, the system for data processing has a camera and a control device connected to the camera.

[0036] The system for data processing may be designed to be installed at least partially in an automated vehicle and / or on board an automated vehicle and / or may be at least partially part of a cloud.

[0037] The system for data processing can be part of a driver assistance system or an automatic driving function or can constitute and / or execute this part. The system for data processing can have an electronic control unit (ECU in English). The data processing device can have an intelligent processor-controlled unit, which can communicate with other modules, for example, via a central gateway (CGW) and can form an on-board network, for example, together with a telematics controller, via a field bus such as a CAN bus, a LIN bus, a MOST bus and a FlexRay or via automotive Ethernet, if necessary. It is conceivable that the controller controls functions related to the driving behavior of the motor vehicle, such as engine control, power transmission, a braking system and / or a tire pressure monitoring system. In addition, driver assistance systems, such as parking assistance, adaptive cruise control (ACC), lane keeping assistance, lane change assistance, traffic sign recognition, light signal recognition, start assistance, night vision assistance, emergency brake assistance and / or intersection assistance can be controlled by the controller.

[0038] It is conceivable that the system for data processing controls the automated driving of the automated vehicle at least partially and / or temporarily based on the output of the environment model.

[0039] What was described above with respect to the method also applies analogously to the data processing system, and vice versa.

[0040] Furthermore, an automated motor vehicle may be provided which has the above-described system for data processing.

[0041] The motor vehicle may be a passenger vehicle, in particular a car.

[0042] The automated motor vehicle may be configured to take over longitudinal guidance and / or lateral guidance at least partially and / or at least temporarily by means of an automated driving function during automated driving of the motor vehicle. The automated driving may be controlled at least partially and / or temporarily by means of an automated driving function by means of a data processing device.

[0043] The automated driving can be performed in such a way that the forward movement of the motor vehicle is performed (largely) autonomously.

[0044] The motor vehicle may be a motor vehicle of level 0 autonomy, ie the driver takes over the task of dynamic driving, even if assisting systems (eg ABS or ESP) are present.

[0045] The motor vehicle may be a Level 1 autonomy motor vehicle, ie having certain driver assistance systems that assist the driver in operating the vehicle, such as an adaptive cruise control (ACC).

[0046] The motor vehicle may be a motor vehicle with a Level 2 autonomy level, ie may be partially automated, such that functions such as automatic parking, lane keeping or lateral guidance, general longitudinal guidance, acceleration and / or deceleration are taken over by a driver assistance system.

[0047] The motor vehicle may be a motor vehicle with a Level 3 autonomy level, i.e., may be conditionally automated so that the driver does not have to constantly monitor the vehicle systems. The motor vehicle autonomously performs functions such as triggering a turn signal, lane change and / or lane keeping. The driver may turn to other things, but if necessary, the system requests to take over the guidance within the warning period.

[0048] The motor vehicle may be a motor vehicle with a level 4 autonomy, ie may be highly automated, so that the control of the vehicle is continuously taken over by the vehicle system. If the system no longer has control over the driving task, the driver may be asked to take over the control.

[0049] The motor vehicle may be a motor vehicle with a Level 5 autonomy level, ie may be fully automated, so that no driver is required to perform the driving task. No human intervention is required except for determining the target and turning on the system.

[0050] The above descriptions regarding the method and the system for data processing also apply analogously to the motor vehicle and vice versa.

[0051] Furthermore, a computer program is provided. The computer program is characterized in that it comprises instructions which, when the program is executed by a computer, cause the computer to at least partially carry out the described method.

[0052] The program code of the computer program may be present as any desired code, in particular a code suitable for motor vehicle control.

[0053] Furthermore, a computer-readable medium, in particular a computer-readable storage medium, is provided. The computer-readable medium is characterized in that it comprises instructions which, when the program is executed by a computer, cause the computer to at least partially execute the method described above.

[0054] That is, a computer-readable medium including the computer program defined above can be provided. The computer-readable medium can be any digital data storage, such as a USB flash drive, a hard drive, a CD-ROM, an SD card or an SSD card. The computer program does not necessarily have to be stored on such a computer-readable storage medium in order to be available to the motor vehicle, but can also be obtained from the outside via the Internet or other means.

[0055] What was described above with respect to the method, the system for data processing and the automated vehicle also applies analogously to the computer program and the computer-readable medium, and vice versa. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Reference below Figure 1 and Figure 2 An implementation scheme is described.

[0057] Figure 1 A schematic top view of a motor vehicle is shown, which is configured to carry out a method for setting an operating state of a driver assistance system, and

[0058] Figure 2 A flow chart of the method is schematically shown. DETAILED DESCRIPTION

[0059] exist Figure 1 The motor vehicle 1 shown in FIG. 1 has an environment camera 2, here a front camera, which is connected to a control unit 3. The (environment) camera 2 and the control unit 3 together form at least part of a system for data processing, which is configured to execute a method for setting an operating state of a driver assistance system, Figure 2 The flow chart of the method is shown in . In this case, the control unit 3 itself is at least part of a driver assistance system and is designed to control the lateral guidance of the motor vehicle 1 based on image data recorded by means of a camera 2 of the motor vehicle 1 .

[0060] As from Figure 2 As can be seen in FIG. 1 , the method mainly includes six steps S1-S6.

[0061] In step S1 of the method, weather conditions in the surroundings of the motor vehicle are determined by means of a camera based on image data. The image data are determined in an optional initial step of the method (in Figure 2 The image is recorded by camera 2 (not shown).

[0062] In a second step S2 of the method, lane markings 4 are identified in the surroundings of motor vehicle 1 and their course is determined based on image data obtained by camera 2 , wherein the first and second steps S1 , S2 can be performed at least partially / temporarily in parallel.

[0063] That is, in steps S1 and S2, the camera 2 identifies, for example, "heavy rain" as a bad weather condition through a weather algorithm. At the same time, the same camera 2 outputs the trend of the lane marking 4, for example in the form of a polynomial or a polyline (or spline).

[0064] In a third step S3 of the method, the determined weather conditions, ie whether good weather conditions or bad weather conditions are currently present, and the determined course of lane markings 4 are output from camera 2 to control unit 3 .

[0065] In a fourth step S4 of the method, control unit 3 determines the length L of recognized lane marking 4 based on the course of lane marking 4 .

[0066] In a fifth step S5 of the method, an operating state of the driver assistance system is set by means of the control unit 3 based on the determined weather conditions and the determined length L of the recognized lane marking 4. Setting the operating state of the driver assistance system includes deactivating or preventing activation of the driver assistance system when the determined length L of the recognized lane marking 4 is below a predetermined threshold and adverse weather conditions are present.

[0067] Here, for example, it can be assumed that in good weather and clearly visible lane markings, the effective length L of the lane marking 4 (and therefore the distance or length L until the lane marking is detected by the camera 2) is, for example, 80 m. In contrast, in bad weather and / or poor lane markings, the effective length L of the lane marking 4 may, for example, only be 20 m. For example, the automatic lateral guidance can be deactivated in advance according to the following table:

[0068] Condition Weather conditions length Operation status to be adjusted 1 Inclement Weather 80m Activate or be able to activate 2 Inclement Weather 20m Deactivated or cannot be activated 3 Good weather 80m Activate or be able to activate 4 Good weather 20m Activate or be able to activate

[0069] In the above-mentioned cases 1, 3 and 4 and when the driver assistance system is activated, in a sixth step S6 of the method, the lateral guidance of the motor vehicle 1 is controlled by the driver assistance system via the control unit 3 based on the image data, wherein the lateral guidance of the motor vehicle 1 is controlled in particular based on the course of the recognized lane markings 4.

[0070] Reference numerals list

[0071] 1 Motor Vehicle

[0072] 2 Cameras

[0073] 3 Control unit or control device

[0074] 4 Lane markings

[0075] L Length

[0076] Steps of the S1-S6 method

Claims

1. A method for setting an operating state of a driver assistance system, the driver assistance system being configured to control a lateral guidance of a motor vehicle (1) based on image data recorded by means of a camera (2) of the motor vehicle (1), the method comprising: - determining weather conditions in the environment of the motor vehicle (1) based on the image data, - recognizing lane markings (4) based on the image data, - determining the length (L) of the identified lane marking (4), and - setting the operating state of the driver assistance system based on the determined weather conditions and the determined length (L) of the recognized lane marking (4). 2 . The method according to claim 1 , wherein adjusting the operating state of the driver assistance system comprises deactivating or preventing activation of the driver assistance system.

3. The method according to claim 2, wherein the driver assistance system is deactivated or activated when the determined length (L) of the identified lane marking (4) is below a predetermined threshold and the determined weather conditions meet predetermined criteria for severe weather conditions.

4. The method according to any one of claims 1 to 3, wherein the method comprises controlling the lateral guidance of the motor vehicle (1) with the aid of the driver assistance system based on the image data in accordance with the set operating state of the driver assistance system. 5 . The method according to claim 4 , wherein the lateral guidance of the motor vehicle ( 1 ) is controlled based on the course of the detected lane markings ( 4 ).

6. The method according to any one of claims 1 to 5, wherein the determination of the weather conditions and / or the recognition and / or determination of the length (L) of the lane marking (4) is performed by the camera (2).

7. A system for data processing, comprising a camera (2) and a control device (3) connected to the camera (2), wherein the system for data processing is configured to perform the method according to any one of claims 1 to 6.

8. A motor vehicle (1) having a system for data processing according to claim 7, wherein the motor vehicle (1) is configured to control the lateral guidance of the motor vehicle (1) based on image data recorded by a camera (2) of the motor vehicle (1).

9. A computer program comprising instructions which, when the computer program is executed by a computer, cause the computer to perform the method according to any one of claims 1 to 6.

10. A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 6.

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