Patent Application
20230347812
This invention is related to the field of automotive lighting devices, and more particularly, to the management of the light patterns provided by these devices.
Digital lighting devices are being increasingly adopted by car makers for middle and high market products.
These digital lighting devices usually comprise solid-state light sources, the operation of which may be customized.
However, sometimes it is not easy to show which parameters are involved in the customization of the light pattern. Sometimes it is difficult to consider all the circumstances involved in lighting the road ahead the vehicle.
The invention provides an alternative solution for providing an optimal light pattern of an automotive lighting device by a method for operating an automotive lighting device according to the invention. Preferred embodiments of the invention are defined in dependent claims.
Unless otherwise defined, all terms (including technical and scientific terms) used herein are to be interpreted as is customary in the art. It will be further understood that terms in common usage should also be interpreted as is customary in the relevant art and not in an idealised or overly formal sense unless expressly so defined herein.
In this text, the term “comprises” and its derivations (such as “comprising”, etc.) should not be understood in an excluding sense, that is, these terms should not be interpreted as excluding the possibility that what is described and defined may include further elements, steps, etc.
In a first inventive aspect, the invention provides a method for operating an automotive lighting device comprising a matrix arrangement of light pixels, the method comprising the steps of:
The term “solid state” refers to light emitted by solid-state electroluminescence, which uses semiconductors to convert electricity into light. Compared to incandescent lighting, solid state lighting creates visible light with reduced heat generation and less energy dissipation. The typically small mass of a solid-state electronic lighting device provides for greater resistance to shock and vibration compared to brittle glass tubes/bulbs and long, thin filament wires. They also eliminate filament evaporation, potentially increasing the lifespan of the illumination device. Some examples of these types of lighting comprise semiconductor light-emitting diodes (LEDs), organic light-emitting diodes (OLED), or polymer light-emitting diodes (PLED) as sources of illumination rather than electrical filaments, plasma or gas.
This method is aimed to find the optimal light pattern to be projected by a lighting device taking into account all the circumstances which may be acquired by an image. Information is therefore acquired directly, without any estimation of the surrounding circumstances. With this method, not only the light projected by other vehicles or objects is considered, but also the particular effects of different climate issues, which may cause light to reflect or refract, thus providing a completely unique luminance map.
In some particular embodiments, the steps of the method are performed periodically with a period lower than 2 seconds, and particularly lower than 0.5 seconds.
This feature involves a quick adaptation to changes in the environmental conditions of the vehicle.
In some particular embodiments, wherein the step of transforming the image data into a luminance map is carried out by a control unit which is previously configured to transform the image data into a luminance map by means of:
This way of training the control unit is useful since provides the control unit with the ability to provide a luminance map in an improved way.
In some particular embodiments, the step of calculating the adapted light pattern is carried out by a control unit which is previously configured to calculate the adapted light pattern by means of:
This way of training the control unit is useful since provides the control unit with the ability to calculate the adapted light pattern in an improved way.
In some particular embodiments, the step of training the control unit comprises the use of a machine learning algorithm.
This machine learning algorithm may be used both in the transformation of the image data into a luminance map and/or in the calculation of the adapted light pattern. Each one of the two options follows its own machine learning algorithm. Once the corresponding results are validated, the values of the control unit are used to the corresponding steps of the method of the invention.
In some particular embodiments, the luminance map isolates the position of the road from the position of other objects in the working zone.
This is very important to define the desired light pattern, since the desired light pattern depends on the size and position of the road.
In some particular embodiments, the image data comprises RGB pixels.
This is a common and simple way to acquire and manage the imaged data captured by the camera.
In some particular embodiments, the image data is acquired by an infrared camera.
Data obtained by infrared camera is sometimes useful in the event of low visibility conditions.
In a further inventive aspect, the invention provides a data processing element comprising means for carrying out the steps of a method according to the first inventive aspect and a computer program comprising instructions which, when the program is executed by a control unit, cause the control unit to carry out the steps of a method according to the first inventive aspect.
In a further inventive aspect, the invention provides an automotive lighting device comprising:
This lighting device provides the advantageous functionality of adapting the light pattern to the conditions transmitted by the data acquired by the camera, in such a way that the new light pattern provided by the control unit improves visual comfort and safety.
In some particular embodiments, the matrix arrangement comprises at least 2000 solid-state light sources.
A matrix arrangement is a typical example for this method. The rows may be grouped in projecting distance ranges and each column of each group represent an angle interval. This angle value depends on the resolution of the matrix arrangement, which is typically comprised between 0.01° per column and 0.5° per column. As a consequence, many light sources may be managed at the same time.
To complete the description and in order to provide for a better understanding of the invention, a set of drawings is provided. Said drawings form an integral part of the description and illustrate an embodiment of the invention, which should not be interpreted as restricting the scope of the invention, but just as an example of how the invention can be carried out. The drawings comprise the following figures:
In In these figures, the following reference numbers have been used:
The example embodiments are described in sufficient detail to enable those of ordinary skill in the art to embody and implement the systems and processes herein described. It is important to understand that embodiments can be provided in many alternate forms and should not be construed as limited to the examples set forth herein.
Accordingly, while embodiment can be modified in various ways and take on various alternative forms, specific embodiments thereof are shown in the drawings and described in detail below as examples. There is no intent to limit to the particular forms disclosed. On the contrary, all modifications, equivalents, and alternatives falling within the scope of the appended claims should be included.
This headlamp 1 is installed in an automotive vehicle 100 and comprises
This matrix configuration is a high-resolution module, having a resolution greater than 2000 pixels. However, no restriction is attached to the technology used for producing the projection modules.
The control unit, previously to its installation in the automotive headlamp, has undergone two training processes.
Both training processes comprise some machine learning steps, where the control unit is trained with training data provided by the plurality of sensors.
The first training process is concerning the transformation of the image data into a luminance map. This first training process comprises
Different image data are provided, and the correspondent luminance map is created, due to the aforementioned algorithm.
The second training process is concerning the calculation of the adapted light pattern. This second training process comprises
In this case, different luminance maps are provided, together with different desired light patterns. The control unit is trained to create the optimal light pattern which, in the particular light circumstances, achieves a final desired light pattern.
Once both training processes are finished, the control unit is installed in an automotive vehicle 100 of
Each 0.2 seconds, the control unit of the lighting device receives an RGB image data which has been acquired by the camera 220. From this image, objects are classified, extracting the road feature 230 and the rest of the objects present in the image. Then, these data is converted into a luminance map 240 by the control unit. The control unit compares the luminance map with the desired light pattern 250 and then creates an adapted light pattern which 260, in combination with the luminance map estimated in the previous steps, provides the user with the desired light pattern.
The headlamp will project the adapted light pattern, which provides an adequate lighting at the minimum power consumption.
This process is repeated each 0.2 seconds.
| Number | Date | Country | Kind |
|---|---|---|---|
| FR2007596 | Jul 2020 | FR | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2021/070174 | 7/19/2021 | WO |
