Method for operating an interior lighting system of a motor vehicle comprising several separately controllable lighting devices and motor vehicle

Abstract

Method for operating an interior lighting (4) of a motor vehicle (1), comprising the steps: - capturing image data (19) relating to the surroundings by at least one imaging sensor (5, 6), each illuminating means (2, 26-30) being assigned a segment (21-25) of the image data (19), each segment comprising at least one pixel (3), - detecting objects (31, 32) depicted in the image data (3), - determining object information (33) which describes a distance (34) and / or a relative speed (35) of the respective detected object (31, 32), - evaluating the object information (33) of the respective detected object (31, 32) to determine whether the respective detected object (31, 32) is selected as the selected object (36), - selecting those illuminants (2, 26-30) whose associated segments (21-25) of the image data (19) do not depict any of the selected objects (36) as the first group (37), and the other illuminants (2, 26-30) as the second group (38), - determining a luminous colour (39) and / or a luminous brightness (40) of the respective illuminant (2, 26-30) of the first group (37) by means of a first processing algorithm (41), and - Determination of a luminous colour (39) and / or a luminous brightness (40) of the respective illuminant (2, 26-30) of the second group (38) by means of a second processing algorithm (42).

Description

[0001] The invention relates to a method for operating a motor vehicle interior lighting system comprising several separately controllable lighting devices. The invention also relates to a motor vehicle.

[0002] Motor vehicles typically include interior lighting, which historically was primarily provided by lights mounted on the vehicle roof. Nowadays, ambient lighting is often used in addition to or as an alternative to such individual light sources. This lighting utilizes a multitude of separate light sources distributed throughout the vehicle interior. The interior ambience can often be customized by using adjustable colors and / or brightness of the light sources.

[0003] Interior lighting can also be dynamically adapted to the driving situation or the vehicle's surroundings. For example, the German patent document DE 10 2021 109 954 A1 proposes adapting the movement of lighting effects to the driving speed and / or controlling the interior lighting depending on the ambient brightness. To adapt to the ambient brightness, the environment can be captured with a camera, after which a low-resolution intermediate image is generated from the camera's image data. The pixels of the intermediate image specify the color and brightness for a light module or for a group of light modules of the interior lighting.

[0004] DE 199 11 648 A1 discloses a method for displaying objects in a vehicle. The relevance of objects is checked using an image evaluation device, and relevant objects are marked and / or highlighted on the display.

[0005] German patent document DE 10 2006 029 510 A1 discloses a motor vehicle with a vision support system. A pillar of the motor vehicle has a display device for displaying an image of the surrounding area obscured by the pillar. The image is distorted depending on the contour of the pillar's surface.

[0006] The document DE 10 2021 109 954 A1 discloses a motor vehicle comprising a central light control unit and a plurality of interior light modules.

[0007] Based on this, the invention is based on the object of further improving the control of an interior lighting depending on the vehicle environment, in particular in order to give vehicle occupants a better impression of the vehicle environment and thus, for example, to enable an improved assessment of the driving situation by the driver.

[0008] The object is achieved according to the invention by a method for operating an interior lighting system of a motor vehicle comprising several separately controllable lighting means, which comprises the following steps: - capturing image data relating to the surroundings of the motor vehicle, comprising a plurality of pixels, by at least one imaging sensor of the motor vehicle, each illuminant being assigned a segment of the image data which in each case comprises at least one of the pixels, - Recognition of objects depicted in the image data, - Determining object information describing a distance of the respective detected object to the motor vehicle and / or a relative speed of the respective detected object with respect to the motor vehicle, based on the image data and / or on the basis of distance data of at least one distance sensor of the motor vehicle, - Evaluating the object information of the respective detected object to determine whether the respective detected object is selected as the selected object, - Selection of those illuminants whose associated segments of the image data do not depict any of the selected objects as the first group of illuminants, and of the illuminants whose associated segments of the image data depict at least one of the selected objects as the second group of illuminants, - Determination of a luminous colour and / or a luminous brightness of the respective illuminant of the first group on the basis of the image data by a first processing algorithm, and - Determining a luminous color and / or a luminous brightness of the respective illuminant of the second group on the basis of the image data by a second processing algorithm different from the first processing algorithm, wherein, on the one hand, a respective image region of the image data is assigned to the respective illuminant, each comprising at least two of the pixels, wherein the image region of the image data assigned to the respective illuminant overlaps with at least one image region assigned to another of the illuminants, wherein the first processing algorithm determines the luminous brightness and / or the luminous color of the respective illuminant of the first group depending on image values ​​of all pixels that lie in the image region of the image data assigned to the respective illuminant,and / or wherein, on the other hand, a color saturation of the respective luminous color of the respective illuminant of the first group determined by the first processing algorithm on the basis of the image data is lower than a color saturation that would result from the determination of the luminous color of this respective illuminant by the second processing algorithm on the basis of the same image data.

[0009] In modern motor vehicles, interior or ambient lighting consisting of many separately controllable light sources is increasingly being used, in which, for example, on at least one interior surface, for example on the inside of a door and / or in the area of ​​the dashboard and / or pillars of the motor vehicle, the light sources are arranged at a short distance from one another, for example at a distance of less than 5 cm or less than 2 cm.If the approach explained at the beginning, in which the lighting means are controlled according to a low-resolution intermediate image generated on the basis of the image data of a camera, is transferred unchanged to such luminous surfaces, the result can be a luminous image that, although it approximately depicts the vehicle surroundings, often has a disturbing and distracting effect on vehicle occupants due to typically unavoidable color errors, perspective errors and errors due to a delayed adaptation of the luminous image.

[0010] Within the scope of the invention, it was recognized that this problem can be avoided or at least significantly reduced by reducing color and / or brightness contrasts between adjacent light sources. This can be achieved by softening the illuminated image, which can lead to a certain blurriness or a frosted glass effect, and / or by reducing the color saturation.

[0011] However, a sufficiently strong alienation of the light pattern by the measures mentioned above in order to avoid disturbing the observer due to the errors and discrepancies explained leads in many situations to typical observers no longer perceiving the resulting light pattern as an image of the surroundings and thus as a kind of transparency of the body in the respective area, whereby the resulting light pattern no longer acts as a relevant source of information.

[0012] However, within the scope of the invention, it was recognized that this problem can be avoided or at least significantly reduced by using a second processing algorithm that is different from the first processing algorithm for those lighting means whose assigned segments depict nearby objects and / or objects that are moving rapidly with respect to the motor vehicle, for example if corresponding objects are depicted in a sharply selectable and / or full-color manner in the light pattern.

[0013] The described process enables advanced interior design, bringing the outside world into sharper focus. This sharpens the overall appearance of the vehicle interior and creates an appealing visual effect. Automatic and situational lighting creates a unique interior feeling within the vehicle. Depending on the driving situation or mood, the lighting can optionally be adjusted accordingly to create a pleasant atmosphere and increase driving comfort.

[0014] The described approach is technically simple and cost-effective to implement, as in many cases the required components are already present in the vehicle. It can therefore be integrated into existing lighting components without requiring extensive modifications to the vehicle. This simplifies the installation process and keeps production costs low. Thus, the described functionality can also be implemented as a "function on demand." This means that additional content can be optionally integrated into the vehicle via download, depending on the needs and preferences of the vehicle owner.

[0015] A segment of the image data can be understood as a, in particular contiguous, group of pixels of the image data or even a single pixel. The segments of the image data are preferably selected such that they do not overlap, i.e., pixels of the image data are each only part of a segment of the image data. In particular, the image data can describe a two-dimensional image whose various segments are assigned to different illuminants. However, it is also possible, for example, for parts of the image to lie outside the segments assigned to the illuminants.

[0016] The distance of the respective detected object from the motor vehicle can be a distance to a reference point of the motor vehicle, which is defined in particular with respect to the imaging sensor or the distance sensor. The distance can be detected by a dedicated distance sensor, for example, an ultrasonic or radar sensor. It is also possible for the imaging sensor to detect distances, for example, a laser scanner or a time-of-flight camera.

[0017] Additionally or alternatively, a distance can be determined based on the image data itself, for example, if it is captured by a stereo camera. The relative speed of the detected object to the vehicle can also be determined as a movement relative to the reference point explained above.

[0018] The image data may, in particular, be a 360° panoramic image of the vehicle's surroundings. Such a panoramic image may, in particular, be composed of sensor data from multiple sensors.

[0019] Each pixel of the image data can be assigned a solid angle of the vehicle's surroundings. Thus, in particular, the respective segment can also be assigned to a solid angle segment of the vehicle's surroundings, which can be formed, in particular, by the combined solid angles assigned to the individual pixels of the segment.

[0020] The assignment of the segments to the illuminants can in particular be carried out in such a way that from a specific observer, for example from a driver's seat of the motor vehicle, the respective solid angle segment is arranged at least approximately in the extension of the respective illuminant, so that with a sufficiently dense arrangement of the illuminants in at least one area of ​​the motor vehicle, in particular an apparent transparency of this area of ​​the motor vehicle can result for the observer.

[0021] A respective image region of the image data can be assigned to the respective illuminant, which in each case comprises at least two of the pixels, wherein the image region of the image data assigned to the respective illuminant overlaps with at least one image region that is assigned to another of the illuminants, wherein the first processing algorithm determines the luminous brightness and / or the luminous color of the respective illuminant of the first group as a function of image values ​​of all pixels that lie in the image region of the image data assigned to the respective illuminant.

[0022] Because the first processing algorithm evaluates overlapping image areas of the image data, overlapping areas result whose pixels influence the luminous intensity and / or luminous color of several of the illuminants. This corresponds, in particular, to a blurring of the image data in the context of determining the luminous intensity and / or luminous color of the illuminants of the first group.

[0023] An overlap of two image regions can be understood in particular to mean that at least one pixel of the image data lies in both image regions. In this case, it is particularly possible for a pixel of the image data to be part of more than two of the image regions, so that more than two of the image regions can overlap in this pixel. The first processing algorithm thus creates in particular a certain blurriness or a frosted glass effect in the illuminated image, as a result of which, as explained above, for example color errors, perspective errors and errors due to a delayed adjustment of the illuminated image are not recognizable by a viewer or are at least significantly less noticeable than with a sharp image.

[0024] The image area assigned to the respective illuminant of the first group comprises, in particular, the segment of the image data assigned to this illuminant and extends beyond this segment. In particular, the respective assigned image area can comprise all pixels of the respective assigned segment as well as additional pixels. The additional pixels can, for example, be located within the segments assigned to neighboring illuminants.

[0025] In an advantageous embodiment, the second processing algorithm determines the luminous colour and / or the luminous brightness of the respective illuminant of the second group as a function of image values ​​exclusively of a respective subgroup of the pixels of the image data, wherein the subgroup - on the one hand, does not comprise a pixel on which the luminous colour and / or the luminous brightness of any of the other luminous means of the second group depends, and / or - on the other hand, contains fewer pixels than the image area of ​​the image data assigned to the respective illuminant, the pixels of which would be taken into account by the first processing algorithm when determining the luminous brightness and / or the luminous colour of the respective illuminant.

[0026] Such a configuration of the second processing algorithm results in an image in the area of ​​illuminants of the second group, i.e., in particular, in areas where a selected object is imaged, without blurring across several of the illuminants, or at least with less blurring than the first processing algorithm. Selected objects, i.e., in particular, objects located close to the motor vehicle and / or moving significantly relative to the motor vehicle, can thus be imaged with high resolution, or at least more sharply, than areas without such objects in the light pattern.

[0027] As already explained above, this makes it clear to an observer, in particular a driver of the motor vehicle or another vehicle occupant, that the resulting light pattern depicts the surroundings, even if other areas of the light image are blurred. The light pattern is thus perceived as a type of transparency of the body and can therefore inform the observer about the vehicle's surroundings. Due to the sharp or slightly blurred representation of selected objects, the positions and movements of these objects that are potentially particularly relevant for driving are also clearly recognizable for the observer. The respective subgroup can, for example, comprise exclusively pixels within the segment of the image data assigned to the respective light source.

[0028] A color saturation of the respective luminous color of the respective illuminant of the first group determined by the first processing algorithm on the basis of the image data is preferably lower than a color saturation that would result from the determination of the luminous color of this respective illuminant by the second processing algorithm on the basis of the same image data.

[0029] As already explained above, by reducing the color saturation it can be achieved that color errors, perspective errors and / or errors due to a delayed adjustment of the illuminated image by a viewer are not recognizable or are at least significantly less noticeable than in an image with higher color saturation, in particular than in an at least approximately true-color image, as can preferably be done to depict the selected objects and thus for the illuminants of the second group.

[0030] The luminous color of a respective illuminant can be determined by the first processing algorithm by reducing a color saturation of a respective intermediate result for the luminous color of the respective illuminant, which is determined by a sub-algorithm of the first processing algorithm on the basis of the image data, by a further sub-algorithm of the first processing algorithm.

[0031] This allows the effect described above to be achieved with minimal effort. Alternatively, for example, color-reduced image data could be initially acquired, on the basis of which a sub-algorithm of the first processing algorithm determines the respective luminous color.

[0032] The sub-algorithm used to determine the intermediate result can, for example, determine the luminous brightness and the intermediate result for the luminous color by averaging the brightnesses and colors of the pixels in the image area explained above and assigned to the respective illuminant or summing them in a generally weighted manner and / or by selecting a respective dominant color or brightness in the respective image area.

[0033] The respective segment of the image data can comprise multiple pixels of the image data. In this case, a reduced-resolution intermediate image can be generated as part of the first and / or second processing algorithm, wherein each pixel of the intermediate image is assigned to one of the segments of the image data, wherein the brightness and / or color of the respective pixel of the intermediate image is determined based on the brightnesses and / or colors of the pixels of the respective assigned segment of the image data.

[0034] Since the segments of the image data, as explained above, are each assigned to one of the illuminants, the intermediate image can be used directly in the second processing algorithm to specify the luminous color and / or luminous brightness of the respective illuminant of the second group by the color or brightness of the respectively assigned pixel of the intermediate image. Alternatively, however, further processing of the intermediate image or the brightness and / or color specified by the respective pixel of the intermediate image can also take place within the second processing algorithm in order to specify the respective luminous brightness and / or luminous colors.For example, depending on a user setting, a color saturation and / or overall brightness can be adjusted and / or the luminous brightness can be scaled depending on a detected ambient brightness and / or even a filtering can be carried out, which, however, is preferably less strong than in the case of the first processing algorithm.

[0035] For example, the first processing algorithm can filter the reduced-resolution intermediate image. If filtering also occurs in the second processing algorithm, the filtering in the first processing algorithm can be more stringent than the filtering in the second processing algorithm, for example, by selecting a lower cutoff frequency for a low-pass filter or by using a larger and / or differently shaped filter kernel.

[0036] Filtering can generate a filtered intermediate image whose brightness and / or color values ​​can be used, for example, immediately or after reducing the color saturation, as the luminous brightness and / or luminous color of a respective light source. As already explained for the second processing algorithm, the luminous brightness or luminous color determined in the first processing algorithm can also be adjusted, for example, depending on ambient brightness and / or user distortion.

[0037] In particular, a dominant color in the respective segment can be selected as the color of the associated pixel in the intermediate image. For example, the respective centroid of the respective spectral distribution in the respective segment can be used as the dominant color, or in the case of a spectral distribution with multiple objectionable maxima, the centroid of the area of ​​the highest maximum or the highest maximum itself. Alternatively, it would be possible, for example, to use the median or mean of the various colors in the associated segment as the color of the respective pixel.

[0038] The brightness of each pixel in the intermediate image preferably corresponds to the mean or median of the brightnesses of the pixels in the associated segment. Alternatively, the brightness of each pixel in the intermediate image can also be determined by the dominant brightness in the associated segment.

[0039] The method can in particular be designed such that the respective detected object is selected or can be selected as a selected object only if the distance of the respective detected object to the motor vehicle reaches or falls below a predetermined distance limit and / or if the relative speed of the respective detected object to the motor vehicle reaches or exceeds a relative speed limit.

[0040] By designing the method in this way, as explained above, objects are selected whose concise representation is particularly relevant to give the viewer an impression of the transparency of the vehicle, or which are potentially particularly relevant for driving.

[0041] The two limit value comparisons can be carried out independently of each other, whereby a detected object can only be selected as a selected object if both the distance limit value is reached or undershot and the relative speed limit value is reached or exceeded.

[0042] Alternatively, however, it would be possible to select both objects for which the distance limit is reached or exceeded and objects for which the relative speed limit is reached or exceeded, or to perform only one of the limit comparisons.

[0043] In a further alternative, it would be possible for a limit value comparison to be carried out exclusively with the distance limit value, whereby the distance limit value is specified as a function of the determined relative speed of the respective object, or for a limit value comparison to be carried out exclusively with the relative speed limit value, whereby the relative speed limit value is specified as a function of the determined distance of the respective object.

[0044] The distance limit is preferably equal to or less than one meter. This limit has proven particularly advantageous during the development of the method.

[0045] The relative speed limit can depend, in particular, on the vehicle's speed and can, for example, be between 30% and 130% of the vehicle's speed. Alternatively, a fixed relative speed limit, for example, between 3 m / s and 20 m / s, can be used.

[0046] In addition to the method according to the invention, the invention relates to a motor vehicle with an interior lighting system comprising a plurality of separately controllable lighting devices, at least one imaging sensor, and a control device. The control device is configured to control the lighting devices in at least one operating mode of the control device according to the method according to the invention for operating an interior lighting system comprising a plurality of separately controllable lighting devices. Optionally, the motor vehicle can comprise a distance sensor to detect and consider distance data, as explained above.

[0047] The features explained for the method according to the invention can be transferred to the motor vehicle according to the invention with the advantages mentioned therein and vice versa.

[0048] The control device can be configured to switch to a further operating mode when a mode change condition evaluating a detected driving situation of the motor vehicle is fulfilled, in which the lighting means are controlled according to a predetermined control pattern or according to a control pattern selected from several predetermined control patterns depending on the driving situation.

[0049] While the above-described method for operating the interior lighting allows for the reproduction of a light pattern in most driving situations that gives vehicle occupants a good impression of the vehicle's surroundings, depending on the specific design of the lighting and its control, it may be advantageous to deviate from the described procedure in certain driving situations.

[0050] An example of such a driving situation is driving through a dark environment with many fine-grained colored light sources. Such an environment occurs, for example, when driving in a city at night, when neon signs or similar objects are present in the vehicle's surroundings. If the method described above were used to control the light sources, relevant information—namely, the presence of many small colored light sources—would not be displayed in this driving situation due to the deliberately induced blur and the assignment of a dominant color in a segment or image area to the light source.

[0051] If, however, an attempt were made to sharply depict the individual small color light sources in the light image, the limited resolution of the light image reproduced by the lamps, especially in conjunction with a limited update rate of the light image, would result in spatial and temporal aliasing of the image of the small color light sources, resulting in a light image that does not accurately reflect the surroundings and appears unflattering. Therefore, it is proposed to fall back to a predefined control pattern or one of several predefined control patterns in certain driving situations.

[0052] The respective control pattern can trigger static control of the lamps, for example illuminating all lamps with the same color and brightness or with a predefined brightness and / or color pattern, or control with a predefined temporal pattern that is repeated periodically, in particular. The predefined control patterns can optionally be independent of image data from the imaging sensor and / or distance data from the distance sensor. However, this image data or distance data can be taken into account when selecting the selected control pattern, for example to select a different control pattern depending on the lighting situation in the vehicle's surroundings, for example to distinguish between bright and particularly colored ambient lighting when driving through a city and a rather dark environment when driving over land.

[0053] In the above example of driving through a city with neon lighting, the selected control pattern can, for example, illuminate small, distributed areas of the interior or ambient lighting with pulsating neon colors, while the remaining light sources and thus large areas of the interior lighting shine white, whereby, for example, a color temperature of the luminous color there can be predetermined by the light temperature of the city lighting.

[0054] The fulfillment of the mode change condition and / or the selection of the selected control pattern can depend on the current time of day and / or ambient brightness and / or a position of the motor vehicle detected by a position sensor and / or the detection of light sources in the image data of the imaging sensor. Based on the aforementioned variables, it can be recognized, in particular, if, due to the arrangement of the lighting means, in particular due to the achievable resolution of the light image, and / or the speed at which the light image can or should be updated, it is advantageous to use the predefined light pattern or one of the predefined light patterns instead of a light pattern updated quasi-continuously depending on the image data.

[0055] Further advantages and details of the invention will become apparent from the following exemplary embodiments and the accompanying drawings. These schematically show: Fig. 1 an embodiment of the motor vehicle according to the invention, Fig. 2 a flowchart of an embodiment of the method according to the invention, and Fig. 3 schematically shows a processing of image data in the embodiment according to Fig. 2.

[0056] Fig. 1 shows a motor vehicle 1 with an interior lighting system 4 comprising several separately controllable lighting devices 2, 26-30 and a control device 9 by which the lighting devices 2, 26-30 can be controlled separately to adjust a respective luminous color 39 and luminous brightness 40. The lighting devices 2, 26-30 can be formed, for example, by light-emitting diodes.

[0057] In the example, the lamps 2 are arranged flat in the area of ​​the side doors. The lamps 26-30 in the example are lamps arranged along a C-pillar of the motor vehicle 1. For the purpose of a simple and easily understandable representation of the following with additional reference to the exemplary flow diagram in Fig. 2, a one-dimensional arrangement of the lamps 26-30 is used in the example, on whose control the following explanation focuses, whereby in a real implementation preferably a respective two-dimensional array of lamps 2, 26-30 can be used in different areas of the motor vehicle 1 in order to reproduce a respective light image there.

[0058] The control of the lamps 2, 26-30 should be carried out at least in one main operating mode of the motor vehicle 1, which is shown in the flow chart in Fig. 2 is implemented by steps S5 to 13, depend on image data 19 relating to the surroundings of the motor vehicle 1. The image data 19 are captured in the example by several imaging sensors 5, 6 of the motor vehicle 1 and can in particular be in the form of a 360° panoramic image.

[0059] Since the control of the individual lighting means 2, 26-30 in the main operating mode in the example should also depend on a distance 34 and a relative speed 35 of objects 31, 32 detected in the image data 19 with respect to the motor vehicle 1, the motor vehicle 1 also comprises distance sensors 7, 8 in order to detect these distances 34 or changes therein.

[0060] In addition, the control of the lamps 2,26-30 in the example depends on the current driving situation 10, for the detection of which further sensors of the motor vehicle 1 can be used, for example the Fig. 1 shown position sensor 15.

[0061] The Fig. The flowchart shown in Figure 2 of the method implemented by the control device 9 for controlling the lighting means 2, 26-30 can be divided into three sections. Steps S5-S13 implement a main operating mode in which the operation of the interior lighting 4 is intended to create the impression of partial transparency of the body of the motor vehicle 1 for a vehicle occupant or observer (not shown). Steps S1 and S2 assess whether this main operating mode is suitable for the current driving situation or whether a fallback to an alternative operating mode implemented by steps S3 and S4 should occur.

[0062] In step S1, a driving situation 10 of the motor vehicle is first recorded. In the example, the current time of day 11, the ambient brightness 12, which can be recorded, for example, via the imaging sensors 5, 6, the position 13 of the motor vehicle 1 recorded by a position sensor 15, and the light sources 14 detected in the image data of the imaging sensors 5, 6 are taken into account.

[0063] In step S2, the fulfillment of a mode change condition 16 is then checked, which evaluates the driving situation 10 detected in step S1.

[0064] In this case, the position 13 of the motor vehicle 1 can be used, for example in conjunction with map data available on the vehicle, to classify the surroundings of the motor vehicle, for example to detect driving through a city, a cross-country journey, driving through a construction site area or the like.

[0065] Based on the time of day 11, determined, for example, by an internal clock or by receiving corresponding radio signals, it is possible to determine whether a night trip is currently taking place. In addition, night tripping can also be detected based on the ambient brightness 12.

[0066] The evaluation of the detected light sources 14 can be used, in particular, to detect when a relatively large number of small light sources 14 are present in the vehicle's surroundings, for example, the neon signs in a city discussed in the general section, or even construction site lighting. As already explained, such light sources typically cannot be reproduced attractively in the main operating mode.

[0067] The mode change condition 16 can be met, for example, when the presence of a large number of small light sources 14 is detected during night driving and the position 11 indicates that these light sources are characteristic of the vehicle environment, for example in a city with neon advertising or when driving through an illuminated construction site.

[0068] In this case, the example reverts to an alternative operating mode. For this purpose, in step S3, several predefined control patterns 17 are provided, which can be defined, for example, by the vehicle manufacturer and / or parameterized by a user of the motor vehicle 1 and describe a desired control of the lighting devices 2, 26-30 for a particular type of driving situation 10. For example, the respective control pattern 17 can specify a fixed light pattern or a periodically repeated sequence of light patterns.

[0069] In step S4, depending on the actual driving situation 10, one of the predetermined control patterns 17 is selected as the selected lighting pattern 18, which is then used to control the lamps 2, 27-30. Thus, for example, as already explained in the general section, when driving at night through a city with neon advertising, essentially white interior lighting can be selected, with a pulsating sequence of neon colors being displayed in individual areas in order to abstractly visualize the existing neon advertising. When driving through a construction site, on the other hand, the brightness of the interior lighting 4 can be selected to be low, with the visual impression of warning lights on a construction site being reinforced, for example, by static or animated orange stripes.

[0070] If, however, the mode change condition 16 is not fulfilled in step S2, the scattering device 9 is operated in the main operating mode, in which the lamps 2, 26-30 of the interior lighting 4 are to be controlled in such a way that a kind of transparency of the body results.

[0071] For this purpose, in the example, each of the illuminants 2, 26-30 is assigned a solid angle segment of the vehicle surroundings and thus also a segment 21-25 of the image data 19 acquired in step S5. The assignment of several pixels 3 of the image data 19 to a respective segment 21-25 or to a respective illuminant 26-30 is shown in Fig. 3 is shown schematically for the illuminants 26-30. To enable a clear representation, the simplified representation is based on one-dimensional image data 19, in which the respective pixel 3 of the image data 19 has only one or two neighbors.

[0072] In real-world applications, two-dimensional image data 19 are typically evaluated. In this case, instead of the shown segments 21-25 each with three pixels 3, segments 21-25 with three pixels in each direction, or a total of nine pixels, could be used. The pixel counts mentioned are purely exemplary, and a suitable assignment can be selected depending on the resolution of the image data and the number of illuminants.

[0073] In principle, it would now be possible to use the same processing algorithm for all light sources 2, 26-30 to determine a luminous brightness and luminous color based on the image data. However, as already discussed in the general section, in this case, a strong blurring of the luminous image would be necessary to prevent typically unavoidable color errors, perspective errors, and / or errors due to a delayed adjustment of the luminous image from disturbing and distracting vehicle occupants. In this case, however, the interior lighting 4 would only be of very limited use in informing vehicle occupants about the vehicle's surroundings, and the resulting luminous image would typically no longer be perceived as transparency of the body.

[0074] Therefore, in steps S5 to S10, the illuminants 2, 26-30 are divided into a first and a second group 37, 38. A different processing algorithm 41 is then used to determine the luminous colors 39 and luminous brightness 40 of the respective illuminants 2, 26-28 of the first group 37 than the one used to determine the luminous brightness 39 and luminous color 40 of the illuminants 29, 30 of the second group 38.

[0075] To support the division of the lighting devices 2, 26-30 into the groups 37, 38, in step S5, in addition to the image data 19, additional distance data 20 is acquired by means of the distance sensors 7, 8, which describe the distance 34 of a respective object 31, 32 arranged in the respective solid angle segment from the motor vehicle or the change in this distance. Angle-resolved radar and / or ultrasonic sensors, for example, can be used as distance sensors 7, 8. In a modification of the motor vehicle 1 shown, it would also be possible to use the imaging sensors 5, 6 themselves as distance sensors, for example if they provide three-dimensional image data. Stereo cameras or laser scanners, for example, could be used as imaging sensors in this case.

[0076] In step S6, various objects 31, 32 depicted in the image data 19 are detected. Any known approaches for object detection in image data, such as the detection of scale-invariant features, edge detection, optical flow determination, or the like, can be used. Optionally, the distance data 20 can also be used as part of the object detection.

[0077] In step S6, object information 33 is then determined for each of the objects 31, 32 detected in the image data. This object information 33 describes the distance 34 of the respective detected object 31, 32 from the motor vehicle 1 and a relative speed 35 of the respective detected object 31, 32 with respect to the motor vehicle 1. In the example, the distance can be directly specified by the distance data 20. To determine the relative movement, both distance changes determined on the basis of the distance data and changes in the solid angle in which the respective object 31, 32 is located, which can be determined on the basis of the image data 19, can be taken into account.

[0078] From the detected objects 31, 32, those objects 36 are then selected in step S8 in the example that are close to the motor vehicle, for example, at a distance of less than 1 m, and that exhibit a certain relative movement with respect to the motor vehicle, for example, at a relative speed of more than 0.5 m / s. In the example, only the detected object 31, i.e., in this example, another motor vehicle, is selected as the selected object 36, since the detected object 32, in the example, a house, is located a great distance from the motor vehicle 1.

[0079] In step S9, those of the segments 21-25 which depict a selected object 36, i.e. in the example the segments 24, 25, are then selected and the illuminants 29, 30 assigned to these segments 24, 25 are assigned to the second group 38.

[0080] The remaining illuminants 2, 26-28 are then assigned in step S10 to the first group 37, which thus comprises those illuminants 2, 26-28 whose assigned segments 21-23 of the image data 19 do not depict any of the selected objects 36.

[0081] A second processing algorithm 42, which determines the luminous color 39 and the luminous brightness 40 of the respective illuminant 29, 30 of the second group 38, is implemented in the example by step S11. There, a reduced-resolution intermediate image 53 is generated. The generation of that part of the intermediate image 53, which is generated from the segments 21-25 of the image data 19, is described in Fig. 3 shown schematically.

[0082] Each pixel 54 of the intermediate image 53 is assigned to one of the segments 21-25 of the image data 19. The brightness and color of the respective pixel 54 of the intermediate image 53 is determined based on the brightnesses and colors of the pixels 3 of the respective assigned segment 21-25 of the image data.

[0083] In the example, the brightness of the respective pixel 54 is determined as the average of the brightnesses of the pixels 3 of the segment 21-25 assigned to the respective pixel 54. In the example, the respective dominant color in the respective assigned segment 21-25 is selected as the color of the respective pixel 54, for example, the center of gravity of a spectral distribution in the segment. Alternative embodiments of this step S11 have already been discussed in the general section and will therefore not be repeated.

[0084] Since each of the pixels 54 of the intermediate image 53 is assigned to a segment 21-25 under a respective illuminant 2, 26-30, the selected object 36 or, in other driving situations, several selected objects can be clearly displayed in the illuminated image by using the brightness and color of a respective pixel 54 of the intermediate image 53 directly to adjust the luminous brightness 39 and the luminous color 40 of the respective illuminant 29, 30 of the second group 38. This is shown in the example in Fig. 3 by the arrows which directly connect the respective associated pixel 54 of the intermediate image 53 with the respective associated illuminant 29, 30 of the second group 38.

[0085] In a variation of the example, the brightness or color specified by the intermediate image could also be further processed beforehand, for example to scale the brightness depending on a user setting or a detected ambient brightness.

[0086] As a result, the second processing algorithm 42 determines the luminous color 39 and the luminous brightness 40 of the respective illuminant 29, 30 of the second group 38 exclusively as a function of image values ​​of a respective subgroup 48, 49 of the pixels 3 of the image data 19, wherein the respective subgroup 48, 49 does not include any pixel 3 on which the luminous color 39 and / or the luminous brightness 40 of any of the other illuminants 28, 29 of the second group 38 depends.

[0087] In the example, the first processing algorithm 41, by which the respective luminous brightness 39 and luminous colors 40 of the illuminants 2, 26-28 of the first group 37 are determined, also includes step S11, i.e. the determination of the intermediate image 53, which can also be carried out jointly for both processing algorithms 41, 42.

[0088] As in Fig. 3 is schematically illustrated by the processing block 55, the brightnesses and colors described by the pixels 54 of the intermediate image 53 are not used directly to control the illuminants 26-28, but rather, a filtering and reduction of the color saturation first takes place. For the sake of simplicity, these steps are explained below only for the one-dimensional case and for the illuminants 26-28. However, since filter algorithms for filtering multi-dimensional image data are well known, the procedure described below can easily be transferred to the two-dimensional case or to the provision of control information for the illuminants 2.

[0089] In step S12, the intermediate image 53 is first filtered to provide the intermediate result 50. In the example, the filtering is performed by calculating the brightness and color of a respective pixel of the intermediate result 50 using a weighted sum of the pixel 54 of the intermediate image 53 assigned to this pixel and the pixel 54 adjacent to it or the pixels 54 adjacent to it of the intermediate image 53. The intermediate result 50 can thus be calculated, for example, by convolving the intermediate image 53 with a suitable convolution kernel.

[0090] This results in the respective pixel of the intermediate result 50 in the example depending on two or three pixels of the intermediate image 53. The intermediate result 50, which was determined by the sub-algorithm 51 of the first processing algorithm 41, could now, in principle, be used directly by using the brightness and color of a respective pixel of the intermediate result 50 to specify the luminous brightness 39 and luminous color 40 of a respective illuminant 2, 26-28 of the first group 37.

[0091] Due to the above-explained dependence of the respective pixel of the intermediate result 50 on several pixels 54 of the intermediate image 53 and the dependence of the respective pixel 54 of the intermediate image 53 on the pixels 3 of a respective segment 21-25 of the image data 19, the luminous brightness 39 and luminous color 40 and thus the control of all illuminants 26-28 that do not depict a selected object 31 are thus dependent on all pixels of the image data 19 that lie in a respective image area 43-45.

[0092] If, in a variation of the example shown, for example, no selected object 31 were present and the second processing algorithm 41 for determining the luminous intensities 39 and the luminous colours 40 for all in Fig.3 are used, the control of the illuminant 26 would depend on all pixels 3 in the image area 43, the control of the illuminant 27 would depend on all pixels 3 in the image area 44, the control of the illuminant 28 would depend on all pixels 3 in the image area 45, the control of the illuminant 29 would depend on all pixels 3 in the image area 46 and the control of the illuminant 30 would depend on all pixels 3 in the image area 47.

[0093] Thus, the first processing algorithm 41 determines the luminous brightness 39 and the luminous color 40 of the respective illuminant 21, 26-30 as a function of image values ​​of all pixels 3 that lie in the image area 43-47 of the image data 19 assigned to the respective illuminant 2, 26-30, wherein the image areas 43-47 overlap one another.

[0094] In comparison, the second processing algorithm, as explained above, determines the luminous color 39 and the luminous brightness 40 exclusively as a function of image values ​​of a respective subgroup 48, 49 of the pixels 3 of the image data 19. In the example, the subgroup 48, 49 comprises only the pixels of the respective segment 24, 25 and thus fewer pixels 3 than the image area 46, 47 assigned to the respective illuminant 29, 30.

[0095] In the example, the intermediate result 50 is further processed in step S13 by reducing the color saturation of the intermediate result 50 for the luminous color 39 of the respective illuminant 2, 26-28 of the first group 37 by a further sub-algorithm 52 of the first processing algorithm 41. The resulting luminous brightnesses 39 and luminous colors 40 can then be used to control the respective illuminant 2, 26-28 of the first group 37.

[0096] The resulting luminous image is thus, on the one hand, softened and, on the other hand, color-reduced in those areas that do not show a selected object 36, while the selected object 36 or even several selected objects 36 are displayed with sharpness and, in particular, color-trueness. As already explained in the general section, this can prevent a disruption of the image impression that would occur with a sharp display of the entire luminous image, without losing information regarding relevant objects or the impression of a partially transparent vehicle interior.

Claims

[1] Method for operating an interior lighting (4) of a motor vehicle (1) comprising a plurality of separately controllable lighting means (2, 26-30), comprising the steps: - capturing image data (19) relating to the surroundings of the motor vehicle (1), which image data comprise a plurality of pixels (3), by at least one imaging sensor (5, 6) of the motor vehicle (1), wherein each illuminant (2, 26-30) is assigned a segment (21-25) of the image data (19), which segment comprises at least one of the pixels (3), - detecting objects (31, 32) depicted in the image data (3), - Determining object information (33) which describes a distance (34) of the respective detected object (31, 32) to the motor vehicle (1) and / or a relative speed (35) of the respective detected object (31, 32) with respect to the motor vehicle (1), on the basis of the image data (19) and / or on the basis of distance data (20) of at least one distance sensor (7, 8) of the motor vehicle (1), - evaluating the object information (33) of the respective detected object (31, 32) to determine whether the respective detected object (31, 32) is selected as the selected object (36), - selecting those illuminants (2, 26-30) whose associated segments (21-25) of the image data (19) do not depict any of the selected objects (36) as the first group (37) of illuminants (2, 26-30), and those illuminants (2, 26-30) whose associated segments (21-25) of the image data (19) depict at least one of the selected objects (36) as the second group (38) of illuminants (2, 26-30), - determining a luminous colour (39) and / or a luminous brightness (40) of the respective illuminant (2, 26-30) of the first group (37) on the basis of the image data (19) by a first processing algorithm (41), and - determining a luminous colour (39) and / or a luminous brightness (40) of the respective illuminant (2, 26-30) of the second group (38) on the basis of the image data (19) by a second processing algorithm (42) different from the first processing algorithm (41), wherein, on the one hand, a respective image area (43-47) of the image data (19) is assigned to the respective illuminant (2, 25-30), which image area comprises at least two of the pixels (3), wherein the image area (43-47) of the image data (19) assigned to the respective illuminant (2, 26-30) overlaps with at least one image area (43-47) assigned to another of the illuminants (2, 26-30), wherein the first processing algorithm (41) determines the luminous brightness (39) and / or the luminous color (40) of the respective illuminant (21, 26-30) of the first group (37) as a function of image values ​​of all pixels (3) that lie in the image area (43-47) of the image data (19) assigned to the respective illuminant (2, 25-30), and / or wherein, on the other hand, a color saturation of the respective luminous color (39) of the respective illuminant (2, 26-30) of the first group (37) determined by the first processing algorithm (41) on the basis of the image data (19) is lower than a color saturation that would result from the determination of the luminous color (39) of this respective illuminant (2, 26-30) by the second processing algorithm (42) on the basis of the same image data (19). [2] Method according to claim 1, characterized by that the second processing algorithm (42) determines the luminous colour (39) and / or the luminous brightness (40) of the respective illuminant (2, 26-30) of the second group (38) as a function of image values ​​exclusively of a respective subgroup (48, 49) of the pixels (3) of the image data (19), wherein the subgroup (48, 49) - on the one hand, does not comprise any pixel (3) on which the luminous colour (39) and / or the luminous brightness (40) of any of the other luminous means (2, 26-30) of the second group (38) depends, and / or - on the other hand, contains fewer pixels (3) than the or an image area (43-47) of the image data (19) assigned to the respective illuminant (2, 26-30), the pixels (3) of which would be taken into account by the first processing algorithm (41) when determining the luminous brightness (39) and / or the luminous color (40) of the respective illuminant (2, 26-30). [3] Method according to one of the preceding claims, characterized bythat the luminous color (39) of a respective illuminant (2, 26-30) is determined by the first processing algorithm (41) in that a color saturation of a respective intermediate result (50) for the luminous color (39) of the respective illuminant (2, 26-30), which is determined by a sub-algorithm (51) of the first processing algorithm (41) on the basis of the image data (19), is reduced by a further sub-algorithm (52) of the first processing algorithm (41). [4] Method according to one of the preceding claims, characterized bythat the respective segment (21-25) of the image data (19) comprises a plurality of pixels (3) of the image data (19), wherein as part of the first and / or the second processing algorithm (41, 42) a reduced-resolution intermediate image (53) is generated, wherein each pixel (54) of the intermediate image (53) is assigned to one of the segments (21-25) of the image data (19), wherein the brightness and / or color of the respective pixel (54) of the intermediate image (53) is determined on the basis of the brightnesses and / or colors of the pixels (3) of the respective assigned segment (21-25) of the image data. [5] Method according to one of the preceding claims, characterized bythat the respective detected object (31, 32) is selected or can be selected as a selected object (36) only if the distance (34) of the respective detected object (31, 32) to the motor vehicle (1) reaches or falls below a predetermined distance limit value and / or if the relative speed of the respective detected object (31, 32) to the motor vehicle (1) reaches or exceeds a relative speed limit value. [6] Method according to claim 5, characterized by that the distance limit is equal to or less than one meter. [7] Motor vehicle with an interior lighting system (4) comprising several separately controllable lighting means (2, 26-30), at least one imaging sensor (5, 6) and a control device (9), characterized bythat the control device (9) is designed to control the lighting means (2, 26-30) in at least one operating mode of the control device (9) according to the method according to one of the preceding claims. [8] Motor vehicle according to claim 7, characterized by in that the control device (9) is designed to change to a further operating mode when a mode change condition (16) evaluating a detected driving situation (10) of the motor vehicle (1) is fulfilled, in which further operating mode the lighting means (2, 26-30) are controlled according to a predetermined control pattern (17) or according to a control pattern (18) selected depending on the driving situation (10). [9] Motor vehicle according to claim 8, characterized bythat the fulfillment of the mode change condition and / or the selection of the selected control pattern depends on a current time of day (11) and / or an ambient brightness (12) and / or a position (13) of the motor vehicle (1) detected by means of a position sensor (15) and / or a detection of light sources (14) in the image data (19) of the imaging sensor (5, 6).

Images