Notice of Pre-AIA or AIA Status
Claims 1-20 are currently presented for Examination.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendment filed on 07/27/2026 has been entered and considered by the examiner. By the
amendment, claims 1-2, 4-6, 7-10 and 15 are amended and claims 16-20 are newly added. Following Applicants arguments and amendments made, Examiner still maintained the prior art rejections and the 101 rejections. New 112(b) rejection is added for claim 14. See office action below for explanation.
Applicant arguments 101 rejection
In Example 39 of the USPTO provided Subject Matter Eligibility Examples, the Office indicates that while some limitations of a claim may be based on mathematical concepts, the claim cannot be directed to mathematical concepts if the claim does not recite any mathematical relationships, formulas or calculations. See Example 39. Similar to Example 39 and in contrast to Example 47 of the USPTO provided Subject Matter Eligibility Examples (which recites the performance of particular algorithms), the pending claims relate to determining and simulating a total light distribution of a pixel headlamp in a night journey of a virtual motor vehicle and do not set forth or describe any particular mathematical relationships, calculations, formulas, or equations using words or mathematical symbols. Rather the claims merely involve a broad array of techniques and/or activities that may involve or rely upon mathematical concepts. Accordingly, it is respectfully submitted that the claims do not recite mathematical concepts and thus are not directed to an abstract idea.
Examiner response
Examiner respectfully disagrees since the pending claims are not like Example 39 but are instead directed to an abstract idea. The pending claims are fundamentally distinct from Example 39. In Example 39, the claimed process is directed to a method for training a neural network through specific physical and spatial manipulation of digital image data (e.g., mirroring, rotating, smoothing, and contrast reduction) to expand a training set. In contrast, the pending claims directly recite manipulating coordinate data, 2D arrays, and data structures to arrive at a "total light distribution." Although the applicant states the claim does not use specific mathematical symbols, the steps of "taking into account all the maximum energization individual light distributions... per coordinate" and calculating total light distribution expressly recite mathematical concepts and calculations (SEE Published Spec [0025]). As MPEP 2106.04(a)(2)(I)(C) states a claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the “mathematical concepts” grouping. Describing a mathematical concept using text (e.g., "determining the total light distribution") rather than mathematical symbols does not change the mathematical nature of the underlying concept. The claim merely takes numerical distribution data as an input and outputs a combined data structure representing simulated light intensity. Because the claim sets forth an abstract mathematical concept without integrating it into a practical application or providing a specific technological improvement to the physical headlamp hardware itself, the claim remains directed to an abstract idea. Furthermore, as mentioned in the rejection of office action, the steps of "receiving” and "determining" multiple data lists are also the concepts that can be performed via mental processes (i.e., human mind calculations or basic pen-and-paper data tracking). The broad invocation of a generic "controller" to perform these steps does not shift the invention out of the judicial exception categories under Step 2A Prong One. The pending claims merely calculate and "simulate a total light distribution... in a night journey of a virtual motor vehicle” is an abstract mathematical simulation. It is not integrated into a practical application since the claim does not recite the additional elements (such as controlling an actual physical pixel headlamp on a physical vehicle to improve vehicle safety). Thus, the 101 rejection is still maintained.
Applicant argument 101
As discussed in the present application, these features provide for improving a total light distribution of a pixel headlamp by reducing the computing time of simulation of a total light distribution of a pixel headlamp in a night journey of a virtual motor vehicle that meets a real-time requirement. It is also respectfully submitted that the foregoing features of claims 1-15 providing the above-described technical improvements, would also provide an inventive concept under Step 2B of the Subject Matter Eligibility Test, for example, because they are unconventional features as discussed below.
Examiner response
Applicant argues that the recited features improve the total light distribution of a pixel headlamp by reducing simulation computing time during a virtual night journey to meet a real-time requirement. Examiner has carefully considered this argument but finds it unpersuasive. The claim, as written, does not recite a practical application or a technological improvement to a physical pixel headlamp or physical vehicle system. Instead, the claim details a simulation method operating entirely within a data-processing environment ("on the controller"). The claim calculates a simulated total light distribution on a "controller" It does not require any physical control of an actual physical pixel headlamp, nor does it alter the physical operation of a motor vehicle. Claim steps involve receiving mathematical data (a two-dimensional array of coordinates, individual light distribution values, and relative energization values) and performing mathematical calculations to organize this data into a data structure and determine a total light distribution. Claim also recites a mental process because the claim recites a series of logical and arithmetic steps that a human could map out on paper using pen. While a reduction in simulation computing time is a desirable algorithmic or software metric, a mathematical calculation or data optimization that merely makes a simulation faster does not, on its own, constitute an improvement to the underlying computer functionality or to an independent technology under Prong 2. Thus, reducing time comes solely from the capabilities of the general-purpose computer. And there is big difference between improvement in computer functionality and using computers as a tool to perform the mental process and mathematical concepts. The use of controller is recited at a high level of generality (i.e., as a generic processor performing a generic computer function) and amount to no more than mere instructions to apply the exception using generic computer components. ((See MPEP 2106.05(f)). An improvement in computation time within a computer model is an optimization of the software algorithm itself, not a structural or physical improvement to a machine or hardware technology. Applicant argues that the features of the claims provide an inventive concept under Step 2B in a conclusory manner with no particular evidence cited. Respectfully, the arguments presented by the applicant are not convincing. The claims remain rejected under 35 U.S.C. § 101 as presented in this office action.
Applicant arguments for prior art rejection
Applicant argues Ruddenklau does not teach “determining a maximum energization data structure taking into account all the maximum energization individual light distributions and the texture, wherein the maximum energization data structure comprises a target coordinates list having target coordinates entries, one light intensity list per target coordinates entry having at least one light intensity entry, and one individual light source identification list per target coordinates entry having at least one identification entry, and wherein the maximum energization data structure at least represents which individual light sources influence the light intensity per coordinate of the texture, and to what extent, at maximum energization.”
Examiner response
Examiner respectfully disagrees. Ruddenklau Figure 5 depicts separate texture representations of the individual LED luminous intensity distribution and “Intensity List” containing LED identifiers and relative operative intensities. Pages 76-79 explain that each individual source texture is addressed using normalized coordinates (u, v) and provides that source’s full-power luminous intensity at the addressed coordinate. Under the broadest reasonable sense, the target text grid supplies the target coordinate entries. For each coordinate (u, v), the corresponding source texture values Tk(u, v) supply the light-intensity entries, and the associated sources indices k supply the individual light source identification entries. These coordinates associated with indexed collections are mapped to the claimed intensity and identification lists. The claimed “lists per target coordinate entry” are mapped to the Ruddenklau coordinate associated indexed collection. At a fixed target coordinate p = (u, v), the individual source textures provide the intensity collection [T1(p), …...Tk(p)]. The corresponding sources indices [1…. K) identify the sources associated with those intensity entries. The common coordinated p associated both collections with the same target-coordinate entry. The claim does not require a different coordinate for each source or physically separate storage for each list. Also see page 76-77- The light distribution Lk of the light source k with k ∈ {1,…K} of an HD headlamp with a total of K individual light sources then has the form Lk ∈ RM× N. The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source k at full power in the discretized direction of the vertical angle. For example, entry l17(100,400) contains the luminous intensity of the light source with index 17. So [l1(m, n)….. lk(m, n)] established the determined a maximum energization data structure. Thus, Ruddenklau teaches processing of each target texel across all individual sources supports this association.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 14 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being incomplete for omitting essential structural cooperative relationships of elements, such omission amounting to a gap between the necessary structural connections. See MPEP § 2172.01. Claim 14 recites “The method according to claim 8, wherein a one- time performance of steps a) through c) is followed by a one-time performance of steps e1) or a one-time performance of steps e1') and e2), and repeated, successive performances of steps e3) through e5).” Claim 14 depends on claim 8 and the omitted structural cooperative relationships are: a one-time performance of steps e1'. Thus, the metes and bounds of the claim(s) are unclear.
Claim Rejections - 35 USC §101
5. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. These claims are directed to an abstract idea without significantly more.
(Step 1) Is the claims to a process, machine, manufacture, or composition of matter?
Claims: 1-14 and 16-20 are directed to method or process that falls on one of statutory category.
Claim: 15 is directed to a non-transitory computer-readable storage medium that falls on one of statutory category that is manufacture.
Step 2A Prong 1
Claim 1 and 15 recites
A method for determining a total light distribution of a pixel headlamp, wherein the pixel headlamp comprises a plurality of individual light sources, and wherein a light intensity of a respective individual light source is influenced by energization of the respective individual light source, comprising the steps of:
a) receiving a texture comprising a two-dimension array having coordinates; (The use of a two-dimensional array, row/column indices as coordinates, and discretization points (sampling) to represent a continuous light distribution is fundamentally a mathematical concept. So, it also falls under the “Mathematical Concepts” of abstract ideas. The computer acts merely as a tool to execute these mathematical calculations. The "texture" in this context is just a data structure (a 2D grid). It is similar to using a spreadsheet or a matrix to represent a map; the abstract idea is the mapping of space into a numerical grid. The act of "providing" this texture can be interpreted as a mental process or a process that can be performed by a human using pencil and paper)
b) receiving a maximum energization individual light distribution for each individual light source on the controller, wherein the maximum energization individual light distribution represents at least the light intensity of the individual light source per coordinate at maximum energization of the individual light source; (A "maximum energization individual light distribution" characterized as a mathematical representation or data set (light intensity per coordinate). So, it also falls under the “Mathematical Concepts” of abstract ideas. The act of "providing" this distribution can be interpreted as a mental process or a process that can be performed by a human using pencil and paper.)
c) determining a maximum energization data structure taking into account all the maximum energization individual light distributions and the texture, wherein the maximum energization data structure comprises a target coordinates list having target coordinates entries, one light intensity list per target coordinates entry having at least one light intensity entry, and one individual light source identification list per target coordinates entry having at least one identification entry, and wherein the maximum energization data structure at least represents which individual light sources influence the light intensity per coordinate of the texture, and to what extent, at maximum energization; (The data structure represents a formulaic relationship where individual light distributions are summed to determine maximum intensity per texture coordinate, which is a mathematical calculation and falls under the mathematical concepts of abstract idea. The creation of a "target coordinates list" linked with "light intensity lists" and "identification lists" is a method of organizing data to facilitate calculation, which is recognized as an abstract idea of mental process)
d) receiving a relative energization value for each individual light source on the controller, wherein the relative energization value represents the energization of the individual light source; (Thus limitation describes a method of representing data ("relative energization value"). This is akin to a mathematical algorithm or a "mental process" (assigning values based on observation) to determine status, which falls under the category of abstract ideas.) and
e) determining the total light distribution, taking into account the maximum energization data structure and the relative energization values of the individual light sources. The process of combining individual light source data (using "relative energization values" and a "maximum energization data structure") to find the total light field relies heavily on mathematical equation see spec para [0020]. So, it falls under the “Mathematical Concepts” of abstract idea)
Step 2A, Prong 2: Does the claim recite additional elements that integrate the judicial exception into a practical application?
In accordance with Step 2A, Prong 2, the judicial exception is not integrated into a practical application. Also, the “receiving…” limitation is merely data gathering step or a generic computer function so which is considered as insignificant extra-solution activity as cited in MPEP 2106.05(g). The additional elements of the controller and a non-transitory computer-readable storage medium is mere instructions to implement an abstract idea on a computer, or merely using a generic computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); The claim is directed to an abstract idea.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
In view of Step 2B, the claim as a whole does not amount to significantly more than the recited exception,
i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. Also, the “receiving…” limitation is merely data gathering step or a generic computer function so which is considered as insignificant extra-solution activity as cited in MPEP 2106.05(g) and have recognized the following computer functions as well‐understood, routine, and conventional functions see MPEP 2106.05(d)(II) i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). The additional elements of the controller and a non-transitory computer-readable storage medium is mere instructions to implement an abstract idea on a computer, or merely using a generic computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); The claim is directed to an abstract idea. Thus, claim 1 and 15 are not patent eligible.
Claim 2 further recites wherein step c) comprises the following steps:c1) creating the target coordinates list without target coordinates entries; and c2) successive processing of all maximum energization individual light distributions, taking into account all coordinates of the texture, comprising:
c2.1) determining the light intensity of the maximum energization individual light distribution on a coordinate of the texture; c2.2) checking whether the target coordinates list has a target coordinates entry at the coordinate of the texture; and performing one of the following: c2.3) in a case of the target coordinates list not having a target coordinates entry at the coordinate, creating the target coordinates entry by adding the coordinate as the target coordinate to the target coordinates list and applying the light intensity list and the individual light source identification list for the corresponding target coordinates entry, wherein the light intensity list comprises the light intensity entry representing the light intensity of the individual light source on the coordinate of the texture, and the individual light source identification list comprises the identification entry identifying the individual light source; or c2.4) in a case of the target coordinates list having a target coordinates entry at the coordinate, adding a further light intensity entry to the light intensity list, and a further identification entry to the individual light source identification list. The steps describe a logical method of organizing information (light intensities and their source identifications at specific coordinates) that a human can perform, with pen and paper. The described process constitutes an abstract idea (specifically a method of organizing/manipulating data) and a mathematical concept because it operates on data (coordinates, intensities) via rules (checking, adding) without creating a transformative, non-abstract technical result. It is similar to a mental, logistical process of auditing light sources on a grid, which falls under the category of abstract ideas (such as algorithms or methods of computation). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 3 further recites wherein, in step c), a maximum energization data structure is provided, which, in the light intensity list, exclusively comprises light intensity entries which exceed a preselected threshold light intensity, and the corresponding individual light source identification lists exclusively comprise identification entries of individual light sources whose light intensity entries exceed the preselected threshold light intensity. This claim limitation is categorized as a Mental Process of an abstract idea. It describes the mental act of reviewing a list and selecting items based on a criterion (threshold), which can be performed in the human mind or with pen and paper. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 4 further recites wherein the method additionally comprises, after step c2.1), the following step:
determining whether the light intensity of the maximum energization individual light distribution on the coordinate exceeds the preselected threshold light intensity and performing steps c2.2) through c2.4) for this coordinate based on the threshold light intensity being exceeded. This claim limitation is categorized as a Mental Process of an abstract idea. It describes the mental act of reviewing a list and selecting items based on a criterion (threshold), which can be performed in the human mind or with pen and paper. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 5 further recites wherein the method additionally comprises step b2) of determining a compressed maximum energization individual light distribution from the maximum energization individual light distribution; wherein the compressed maximum energization individual light distribution represents at least the light intensity of the individual light source in a coordinate region that is irradiated by the individual light source at maximum energization in such a way that the light intensity exceeds a second preselected threshold light intensity or a threshold light intensity based upon a preselected percentage threshold value, and wherein, in step c), the maximum energization data structure is determined taking into account all the compressed maximum energization individual light distributions. and mental processes (MPEP 2106.04(a)(2)). The step b2) defines a process of manipulating data (compressed maximum energization individual light distribution) based on thresholding light intensity, which is a mathematical calculation (comparing values and applying percentages) that can be performed in the human mind or with a pen and paper. The determination of a compressed maximum energization individual light distribution is an abstract idea because it describes a method of "organizing information" through mathematical manipulation (thresholding/filtering) of data rather than a physical alteration of the light source itself. It is a mathematical concept (data filtering) and a mental process (a calculation that can be done with pen and paper) that qualifies as an abstract idea under Step 2A Prong 1. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 6 further recites wherein the compressed maximum energization individual light distribution is determined by an edge detection algorithm; or wherein the determination of the compressed maximum energization individual light distribution comprises determining an effectively illuminated, rectangular coordinate region by the following steps: receiving a scattered light-reduced maximum energization individual light distribution by reducing a scattered light component in the maximum energization individual light distribution; determining a maximum light intensity and a coordinate having the maximum light intensity in the scattered light-reduced maximum energization individual light distribution; determining the threshold light intensity taking into account the maximum light intensity and the preselected percentage threshold value; and determining the effectively illuminated, rectangular coordinate region, taking into account the scattered light-reduced maximum energization individual light distribution, the coordinate having the maximum light intensity, and the threshold light intensity. The claim describes a method of evaluating data to find a rectangle, which is a process of mental steps (mental process) and calculations (mathematical concept). It is an abstract idea because it describes a process that can be performed in the human mind, or by a human using a pen and paper. The additional elements of the controller is mere instructions to implement an abstract idea on a computer, or merely using a generic computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 7 further recites wherein the method additionally comprises, after step d), the following steps:
d1) creating a target coordinates buffer from the target coordinates list, a light intensity buffer from all the light intensity lists, and an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure (22), wherein the target coordinates buffer contains a number of ZK elements which corresponds to the number of target coordinates entries of the target coordinates list, and the target coordinates buffer comprises a starting point and a length specification for each ZK element; The step involves organizing data (Target coordinates, intensity, IDs) into buffers, which can be performed in the human mind or on a general-purpose computer using standard data structures. The additional elements of d2) storing the target coordinates buffer, the light intensity buffer, and the individual light source identification buffer is an insignificant extra-solution activity, as it is merely a repository for the data generated by the mental process and are basic computer functions that is well‐understood, routine, and conventional functions see MPEP 2106.05(d)(II)(iv) Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; The additional elements of the controller is mere instructions to implement an abstract idea on a computer, or merely using a generic computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 8 further recites wherein the-step e) comprises: e1) creating a target coordinates buffer from the target coordinates list, a light intensity buffer from all the light intensity lists, and an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure, wherein the target coordinates buffer contains a number of ZK elements which corresponds to the number of target coordinates entries of the target coordinates list, and the target coordinates buffer comprises a starting point and a length specification for each ZK element; e2) transmitting the target coordinates buffer, the light intensity buffer , and the individual light source identification buffer to a graphics card of the controller; e3) creating an energization value buffer from the relative energization values; e4) transmitting the energization value buffer to the graphics card of the controller; and e5) determining the total light distribution by using the graphics card of the controller, taking into account the target coordinates buffer, the light intensity buffer, the individual light source identification buffer, and the energization value buffer. The steps (e1-e5) describe creating buffers (elements, intensities, ID data) and performing calculations to "determine the total light distribution". This is a mathematical manipulation of data structures (buffers) to simulate a physical phenomenon (light), which is a "method of organizing human activity" or "mathematical concept". The computer and graphics card are used as tools to perform these calculations, but the essence of the steps is the calculation itself, not a physical transformation of a tangible object. Also, transmitting step is recognized as computer functions that is well‐understood, routine, and conventional functions see MPEP 2106.05(d)(II) i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 9 further recites wherein, in step e5), a computer shader having shading units is used, wherein each shader unit processes one ZK element in isolation, and/or wherein execution strings of the computer shader run in parallel on several shader units of the graphics card. It is merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f); Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 10 further recites wherein the maximum energization individual light distribution received in step b) represents an item of color information of the individual light source per coordinate, in addition to the light intensity of the individual light source per coordinate, and a light-intensity list of the maximum energization data structure comprises a combined light intensity-color information entry. The process of taking light intensity and color information for individual light sources per coordinate and organizing it into a "combined light intensity-color information entry" is a way of organizing information. This type of data manipulation or mathematical calculation can be performed mentally or with pen and paper. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 11 further recites a one-time performance of steps a) through c) is followed by repeated, successive performance of steps d) and e). This is a mental process or mathematical algorithm (repetitive, iterative manipulation of numbers) that could be done by a person with a pencil and paper, thus falling under the "mental processes" or "mathematical concepts" category of abstract ideas. See also claim 1. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 12 further recites wherein the pixel headlamp comprises more than 200 individual light sources. It is no more than generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h). Also, this is adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g) for mere data gathering. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 13 further recites wherein the method is for simulating a total light distribution of a pixel headlamp in a night journey of a virtual motor vehicle. It is viewed as a mathematical concept or a mental process that can be performed in the human mind (e.g., calculating light angles and intensities with pen and paper,) or via generic computer programming. The use of algorithms and calculations to simulate a physical phenomenon in a virtual space, recite an abstract idea. Also, it is no more than generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 14 further recites wherein a one-time performance of steps a) through c) is followed by a one-time performance of steps e1) or a one-time performance of steps e1′) and e2), and repeated, successive performances of steps e3) through e5). This is a mental process or mathematical algorithm (repetitive, iterative manipulation of numbers) that could be done by a person with a pencil and paper, thus falling under the "mental processes" or "mathematical concepts" category of abstract ideas. See also claim 8. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 16 further recites wherein step e) comprises: el') loading, by the controller, a stored target coordinates buffer, a stored light intensity buffer, and a stored individual light source identification buffer; e2) transmitting the target coordinates buffer, the light intensity buffer, and the individual light source identification buffer to a graphics card of the controller; e3) creating an energization value buffer from the provided relative energization values; e4) transmitting the energization value buffer to the graphics card of the controller; e5) determining the total light distribution by using the graphics card of the controller, taking into account the target coordinates buffer, the light intensity buffer, the individual light source identification buffer, and the energization value buffer. The steps (e3 and e5) describe creating buffers (an energization value buffer) and performing calculations to "determine the total light distribution". This is a mathematical manipulation of data structures (buffers) to simulate a physical phenomenon (light), which is a "method of organizing human activity" or "mathematical concept". The computer and graphics card are used as tools to perform these calculations, but the essence of the steps is the calculation itself, not a physical transformation of a tangible object. Also, the additional elements of loading and transmitting step are recognized as computer functions that is well‐understood, routine, and conventional functions see MPEP 2106.05(d)(II) i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014). Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 17 further recites wherein the relative energization value for each individual light source is generated based on a first simulation condition. A person can look at a simulated chart of conditions, apply a specific formula or ratio, and write down an "energization value" on a piece of paper, thus falling under the "mental processes" category of abstract ideas. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 18 further recites wherein a size of the maximum energization data structure is determined based on a number of overlapping regions between the maximum energization individual light distributions. A person can count the overlapping regions of light on a diagram and calculate a data size using a pencil and a piece of paper, thus falling under the "mental processes" of abstract ideas. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 19 further recites wherein the maximum energization data structure is tailored to an architecture of the controller, and wherein determining the total light distribution further comprises: preprocessing, by the controller, the maximum energization data structure before receiving the relative energization values; receiving, by the controller, a second relative energization values after determining the total light distribution based on a second simulation condition and determining, by the controller, an updated total light distribution based on the second relative energization values using a single cycle. The claim is directed to the abstract idea of a mental process and mathematical modeling (calculating light distribution based on data structures and simulation conditions). The steps of "preprocessing," "receiving," and "determining" describe mathematical manipulations of data that can be performed in the human mind or via pen and paper. The physical components recited—a "controller"—are generic computer hardware performing routine, conventional functions (receiving and processing data) and are recognized as computer functions that is well‐understood, routine, and conventional functions see MPEP 2106.05(d)(II) i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) The limitation of doing this in a "single cycle" merely describes the inherent speed of a fast processor, which does not constitute "significantly more" than the abstract idea itself. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim 20 further recites wherein both the first simulation condition and the second simulation condition are determined based on night journey conditions. A person can logically map, evaluate, or determine these simulation conditions such as (e.g., "If it is nighttime, then set the simulation visibility to 10% and headlights to ON"), this as a step that can be performed entirely in the human mind, thus falling under the "mental processes" of abstract ideas. Claim therefore, when taken as a whole, still does not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception. Claim recites unpatentable ineligible subject matter for the same reasoning and analysis as mentioned for claim 1.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
6. Claim(s) 1-2, 10-13 and 15-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Rüddenklau et al. "Real-Time Lighting of High-Definition Headlamps for Night Driving Simulation." International Journal On Advances in Systems and Measurements 12.3 & 4 (2019): 72-88.
Regarding claim 1
Rüddenklau teaches a method for determining a total light distribution of a pixel headlamp by controller wherein the pixel headlamp comprises a plurality of individual light sources and wherein a light intensity of the individual light source is influenced by energization of the individual light source, (see page 73-74-HD systems are characterized by a great number of independent controllable light sources. Their illumination areas concentrate on sharply defined solid angle intervals with small overlapping areas. The total light distribution of such a headlamp result from the superposition of all the individual light distributions. The individual light distributions are measured with running the corresponding LEDs at full power. During normal operation, the LEDs can be dimmed independently of each other in the range of 0-100% by specifying their electrical currents. For testing the simulation technique presented in this contribution, the HD84-Matrix-LED headlamp developed by HELLA is used. see page 76- The entirety of their values at a given point in time is referred to below as the intensity list. These are specified in the real vehicle by the headlamp control unit, depending on the traffic situation detected by the sensors (see lower left area of Figure 5)) comprising the steps of:
a) receiving, by the controller, a texture comprising a two- dimension array having coordinates (see fig 5 and page 76- In concrete terms, each luminous intensity distribution is converted into a texture, as illustrated in the upper left area of Figure 5. see para 77-78 and fig 6-7-As a consequence, the texture contains 900x900 data points, which are also called texels. Another important point is the indexing of textures. Figure 6 can be used for understanding. Texture coordinates or uv coordinates are always used normalized. If the uv coordinates correspond exactly to a texel of the texture, its value can be returned unchanged. The condition or this is that u M and v N are elements of the natural numbers. In the other case, the neighboring texels of the access coordinates (u; v) must be found first, which are designated by tll; tlr; tul and tur in Figure 7.)
b) receiving, by the controller, a maximum energization individual light distribution for each individual light source on the controller, wherein the maximum energization individual light distribution represents at least the light intensity of the individual light source per coordinate at maximum energization of the individual light source, (see page 74-75-In order to simulate the light distribution of a HD headlamp in any situation, the characteristics of the emitted light must be known for each individual light source in it. Therefore, the luminous intensity distribution is measured for each light source, in concrete terms 95 times, of the headlamp and especially for each LED of the HD84-Matrix. The individual light distributions are measured with running the corresponding LEDs at full power. See page 76-The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source k at full power in the discretized direction of the vertical angle.)
c) determining, by the controller, a maximum energization data structure taking into account all the maximum energization individual light distributions and the texture wherein the maximum energization data structure comprises a target coordinates list having target coordinates entries, one light intensity list per target coordinates entry having at least one light intensity entry, and one individual light source identification list per target coordinates entry having at least one identification entry, and wherein the maximum energization data structure at least represents which individual light sources influence the light intensity per coordinate of the texture and to what extent, at maximum energization, (Ruddenklau Figure 5, 8 and Pages 76-79-The light distribution Lk of the light source k with k ∈ {1,K} of an HD headlamp with a total of K individual light sources then has the form Lk ∈ RM× N. The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source k at full power in the discretized direction of the vertical angle. For example, the entry l17(100,400) contains the luminous intensity of the light source with index 17. Thus, Ruddenklau teaches processing of each target texel across all individual sources supports this association.
Examiner note: page 76-79 explains that each individual source texture is addressed using normalized coordinates (u, v) and provides that source’s full-power luminous intensity at the addressed coordinate. Under the broadest reasonable sense, the target text grid supplies the target coordinate entries. For each coordinate (u, v), the corresponding source texture values Tk(u, v) supply the light-intensity entries, and the associated sources indices k supply the individual light source identification entries. These coordinates associated with indexed collections are mapped to the claimed intensity and identification lists. The claimed “lists per target coordinate entry” are mapped to the Ruddenklau coordinate associated indexed collection. At a fixed target coordinate p = (u, v), the individual source textures provide the intensity collection [T1(p), …...Tk(p)]. The corresponding sources indices [1…. K) identify the sources associated with those intensity entries. The common coordinated p associated both collections with the same target-coordinate entry. The claim does not require a different coordinate for each source or physically separate storage for each list. Thus, it teaches a maximum energization data structure.
d) receiving, by the controller, a relative energization value for each individual light source on the controller, wherein the relative energization value represents the energization of the individual light source, (see page 76-Once both, the individual light distributions and the temporary intensity list, are available, the total light distribution can be calculated. This can be achieved by adding the individual light distributions weighted by the relative current values. see page 78-relative current value ik 2 [0; 1] of individual light source k) and
e) determining, by the controller, the total light distribution taking into account the maximum energization data structure and the relative energization values of the individual light sources. (see page 76 and fig 5-)
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Regarding claim 15
Rüddenklau a teaches a non-transitory computer-readable medium having processor-executable instructions for determining a total light distribution of a pixel headlamp via a controller, wherein the pixel headlamp comprises a plurality of individual light sources, and wherein a light intensity of a respective individual light source is influenced by energization of the respective individual light source, and wherein the processor-executable instructions, when executed, facilitate (see page 73-74-HD systems are characterized by a great number of independent controllable light sources. Their illumination areas concentrate on sharply defined solid angle intervals with small overlapping areas. The total light distribution of such a headlamp result from the superposition of all the individual light distributions. The individual light distributions are measured with running the corresponding LEDs at full power. During normal operation, the LEDs can be dimmed independently of each other in the range of 0-100% by specifying their electrical currents. For testing the simulation technique presented in this contribution, the HD84-Matrix-LED headlamp developed by HELLA is used. See page 76- The entirety of their values at a given point in time is referred to below as the intensity list. These are specified in the real vehicle by the headlamp control unit, depending on the traffic situation detected by the sensors (see lower left area of Figure 5. See also table 1)
The rest of the claim limitation is like claim 1, thus rejected for the same reason as claim 1.
Regarding claim 2
Rüddenklau further teaches wherein step c) comprises the following steps:
c1) creating the target coordinates list without target coordinates entries; and c2) successive processing of all maximum energization individual light distributions, taking into account all coordinates of the texture, (see page 79- After completion of the shader operations for all texels, the target texture contains the contribution of the light source k within the total light distribution, whereby a single component of the sum in the data flow visualized by Figure 9 is mapped. In order to obtain the complete light distribution of the headlamp, all texels of the render target Tcomb are first initialized with 0. Then the Cookie Combiner is applied to the target texture repeatedly with iterating through all individual light sources by changing the parameters Tk and ik.)
comprising:
c2.1) determining the light intensity of the maximum energization individual light distribution on a coordinate of the texture; (See page 76-The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source k at full power in the discretized direction of the vertical angle. see page 79-In the first step within processing, the shader reads the light intensity value tuv of the given individual light texture Tk at position (u; v) corresponding to the texel to be written to in the render target (line 1).)
c2.2) checking whether the target coordinates list has a target coordinates entry at the coordinate of the texture; and performing one of the following: c2.3) in a case of the target coordinates list not having a target coordinates entry at the coordinate, creating the target coordinates entry by adding the coordinate as the target coordinate to the target coordinates list and applying the light intensity list and the individual light source identification list for the corresponding target coordinates entry, wherein the light intensity list comprises the light intensity entry representing the light intensity of the individual light source on the coordinate of the texture, and the individual light source identification list comprises the identification entry identifying the individual light source; or c2.4) in a case of the target coordinates list having a target coordinates entry at the coordinate, adding a further light intensity entry to the light intensity list, and a further identification entry to the individual light source identification list. (See page 79-After completion of the shader operations for all texels, the target texture contains the contribution of the light source k within the total light distribution, whereby a single component of the sum in the data flow visualized by Figure 9 is mapped. In order to obtain the complete light distribution of the headlamp, all texels of the render target Tcomb are first initialized with 0. Then the Cookie Combiner is applied to the target texture repeatedly with iterating through all individual light sources by changing the parameters Tk and ik. The rendering is done with additive blending (see Figures 8 and 9) so the previous values in the render target are not overwritten by the returns of the shader but added to it)
Regarding claim 10
Rüddenklau further teaches wherein the maximum energization individual light distribution received in step b) represents an item of color information of the individual light source per coordinate, in addition to the light intensity of the individual light source per coordinate, and a light-intensity list of the maximum energization data structure comprises a combined light intensity-color information entry.(see page 76-77, see fig 5, 8- This uses the total light distribution determined by the Cookie Combiner and, using a lighting model, determines the color pixel by pixel, which results from the object and light properties as well as the geometric relationships. The individual entries of the texture encode the color at the respective place then typically in the 3 RGB channels (red, green, blue) and a 4th transparency channel (_ channel). In this case, textures are used to encode light intensity distributions. As a consequence, the texture contains 900x900 data points, which are also called texels. Using the same resolution as the measured luminous intensity distributions, each texel corresponds directly to a measuring point of the distribution. In classic color textures the values of the R, G, B and A channels of a texel are encoded with 8 bit fixed-point, whereby each texel contains 32-bit information (RGBA32 texture).)
Regarding claim 11
Rüddenklau further teaches wherein a one-time performance of steps a) through c) is followed by repeated, successive performance of steps d) and e). (See page 76 and fig 5-In concrete terms, each luminous intensity distribution is converted into a texture, as illustrated in the upper left area of Figure 5. See page 74-The individual light distributions are measured with running the corresponding LEDs at full power. See page 79-After completion of the shader operations for all texels, the target texture contains the contribution of the light source k within the total light distribution, whereby a single component of the sum in the data flow visualized by Figure 9 is mapped. In order to obtain the complete light distribution of the headlamp, all texels of the render target Tcomb are first initialized with 0. Then the Cookie Combiner is applied to the target texture repeatedly with iterating through all individual light sources by changing the parameters Tk and ik. The rendering is done with additive blending (see Figures 8 and 9) so the previous values in the render target are not overwritten by the returns of the shader but added to it)
Regarding claim 12
Rüddenklau further teaches wherein the pixel headlamp comprises more than 200 individual light sources. (See page 72 and section Introduction-With this technology, resolutions of several tens of thousands up to a million pixels can be achieved. See page 74- The variety of the representable light distributions is limited only by the resolution of the headlamp, which can range from approx. 100 to several 10,000 pixels, and the permissible values of the electrical current depending on the light technology used)
Regarding claim 13
Rüddenklau further teaches wherein the method is for simulating a total light distribution of a pixel headlamp in a night journey of a virtual motor vehicle. (See abstract- Introducing high-definition headlamp systems in the automotive industry opens up a wide range of possibilities for improving existing and developing new types of dynamic lighting functions. Due to the complexity and subjectivity of light distributions of modern headlamp systems, simulation-based development is indispensable. This contribution presents a first real-time simulation of high-definition systems in virtual environments. As it turns out, the presented implementation is well suited in terms of appearance and computational performance as a basis for a night driving simulation.)
Regarding claim 16
Rüddenklau further teaches the method of claim 1. It further teaches wherein step e) comprises: el') loading, by the controller, a stored target coordinates buffer, a stored light intensity buffer, and a stored individual light source identification buffer; (see page 76 and fig 5-Adiscretized light distribution can be interpreted as a matrix. See page 78 and fig 8-More precisely, the render target of the Cookie Combiner-Shader is a texture Tcomb with the same type and dimensions as the textures of the individual light distributions - a scalar floating-point texture with 900x900 texels. See page 79-80- The other parameter represents the relative intensity ik with which this light source is currently operated. Its code is executed for each texel of the render target Tcomb in parallel (see lower area of Figure 8), whereby the individual threads can be distinguished by further inherent parameters u and v constituting the normalized coordinates of the thread specific texel of the render target. Their common render target is the light buffer, visualized in the lower area of Figure 10. see page 76-The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source. See page 79-80- In the first step within processing, the shader reads the light intensity value tuv of the given individual light texture Tk at position (u; v) corresponding to the texel to be written to in the render target (line 1). Their common render target is the light buffer, visualized in the lower area of Figure 10) . see page 78- Once a way has been found to digitally map luminous intensity distributions to a graphics card compatible manner, the next step is to determine the total light distribution from the individual ones. see page 86 and table I-The results discussed below were recorded on a mobile PC, whose specification can be found in Table I.))
e2) transmitting the target coordinates buffer, the light intensity buffer, and the individual light source identification buffer to a graphics card of the controller; (see page 78- Once a way has been found to digitally map luminous intensity distributions to a graphics card compatible manner, the next step is to determine the total light distribution from the individual ones see page 86- The analysis in the profiler shows that combining the 95 floating point textures on the CPU requires an average of 0.45ms (min: 0.27ms, max: 0.64ms). With cookie combining, however, the CPU acts primarily as the client of the GPU. It instructs the graphics card to execute the Cookie Combiner shader by creating draw calls and defines the relevant context information, such as the render target or the current individual light distribution. See fig 8)
e3) creating an energization value buffer from the provided relative energization values; (see page 86-All relative current values are randomly selected between 0% and 100% for each calculation. See fig 8 –(weighting ik))
e4) transmitting the energization value buffer to the graphics card of the controller; (see page 86- The analysis in the profiler shows that combining the 95 floating point textures on the CPU requires an average of 0.45ms (min: 0.27ms, max: 0.64ms). With cookie combining, however, the CPU acts primarily as the client of the GPU. It instructs the graphics card to execute the Cookie Combiner shader by creating draw calls and defines the relevant context information, such as the render target or the current individual light distribution. See fig 8) and
e5) determining the total light distribution by using the graphics card of the controller, taking into account the target coordinates buffer, the light intensity buffer, the individual light source identification buffer, and the energization value buffer. (SEE PAGE 79-the Cookie Combiner is applied to the target texture repeatedly with iterating through all individual light sources by changing the parameters Tk and ik. The rendering is done with additive blending (see Figures 8 and 9), After applying the Cookie Combiner to all individual light sources k = 1; : : : ;K, the render target Tcomb contains the total luminous intensity distribution. See page 86- So it is not surprising that the GPU has a significantly higher average calculation time of 4.61ms (min: 4.44ms, max: 4.73ms).)
Regarding claim 17
Rüddenklau further teaches wherein the relative energization value for each individual light source is generated based on a first simulation condition. (see section III- The implementation presented here sets the basis for virtual night drives with high-resolution systems and thus creates the possibility to develop and test these simulation-based. For implementing the visualization of the night drive, we used the development environment Unity3D. For this purpose, a system is defined whose input variables represent the relative electrical current values ik ∈ [0,1] of the individual light sources normalized to their maximum value. In addition to the individual light distributions, the relative current values of all light sources are necessary to determine the overall light distribution. The entirety of their values at a given point in time is referred to below as the intensity list. These are specified in the real vehicle by the headlamp control unit, depending on the traffic situation detected by the sensors (see lower left area of Figure 5). This updates the current values with a frequency of 50Hz. see para 86- Each individual light distribution is weighted with the present relative current value. In order to provide the optimum overall light distribution in every driving situation, the current values can be adjusted with a frequency of 50 Hz.))
Regarding claim 18
Rüddenklau further teaches wherein a size of the maximum energization data structure is determined based on a number of overlapping regions between the maximum energization individual light distributions. (see section II-D systems are characterized by a great number of in dependent controllable light sources. Their illumination areas concentrate on sharply defined solid angle intervals with small overlapping areas. The total light distribution of such a headlamp results from the superposition of all the individual light distributions. This architecture enables the generation of highly dynamic overall light distributions by independently controlling the electrical current of each individual light source IN THE headlamp.)
Regarding claim 19
Rüddenklau further teaches wherein the maximum energization data structure is tailored to an architecture of the controller, (See section III- In addition to the individual light distributions, the relative current values of all light sources are necessary to determine the overall light distribution. The entirety of their values at a given point in time is referred to below as the intensity list. These are specified in the real vehicle by the headlamp control unit, depending on the traffic situation detected by the sensors (see lower left area of Figure 5).)
and wherein determining the total light distribution further comprises: preprocessing, by the controller, the maximum energization data structure before receiving the relative energization values; (see fig 8 and see section III- The entry lk(m,n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source k at full power in the discretized direction of the vertical angle ϕm and the horizontal angle θn in Candela. . In contrast to the matrices L1,...,LK, these values are time-dependent signals coming from the headlight control unit at 50 Hz. See fig 8-the maximum energization data structure before ik was inserted. a weighted composition of all individual light distributions. Formally, the output variable corresponds to a L matrix whose dimensions are identical to the dimensions of the individual distributions L1, ...,LK)
receiving, by the controller, a second relative energization values after determining the total light distribution based on a second simulation condition ((see section III- The implementation presented here sets the basis for virtual night drives with high-resolution systems and thus creates the possibility to develop and test these simulation-based. For implementing the visualization of the night drive, we used the development environment Unity3D. For this purpose, a system is defined whose input variables represent the relative electrical current values ik ∈ [0,1] of the individual light sources normalized to their maximum value. In addition to the individual light distributions, the relative current values of all light sources are necessary to determine the overall light distribution. The entirety of their values at a given point in time is referred to below as the intensity list. These are specified in the real vehicle by the headlamp control unit, depending on the traffic situation detected by the sensors (see lower left area of Figure 5). This updates the current values with a frequency of 50Hz. see para 86- Each individual light distribution is weighted with the present relative current value. In order to provide the optimum overall light distribution in every driving situation, the current values can be adjusted with a frequency of 50 Hz.)
and determining, by the controller, an updated total light distribution based on the second relative energization values using a single cycle. (see section III- Once both, the individual light distributions and the temporary intensity list, are available, the total light distribution can be calculated. This can be achieved by adding the individual light distributions weighted by the relative current values. Due to the time dependence of the current values, the total light distribution also varies with time, so that it must be recalculated with the update rate of the intensity list. To be able to perform this calculation 50 times per second, it is carried out in a highly parallel manner using a shader on the GPU)
Regarding claim 20
Rüddenklau further teaches wherein both the first simulation condition and the second simulation condition are determined based on night journey conditions.( See section I- Motivated by this, the idea of a simulation-based virtual night drive was born. In addition to the simulator interface, this requires in a first step the physically precise simulation of the ego vehicle (vehicle, which defines the driver’s view) and in particular the headlight emitted by it, the other road users, the scenery, which includes the road, roadside elements, urban buildings, etc., and the weather conditions in real-time. see section III- The implementation presented here sets the basis for virtual night drives with high-resolution systems and thus creates the possibility to develop and test these simulation-based. For implementing the visualization of the night drive, we used the development environment Unity3D)
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
7. Claim(s) 3-6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rüddenklau et al. ("Real-Time Lighting of High-Definition Headlamps for Night Driving Simulation." International Journal on Advances in Systems and Measurements 12.3 & 4 (2019): 72-88) in view of Waldner et al. ("Hardware-in-the-loop-simulation of the light distribution of automotive matrix-led-headlights." 2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2019.)
Regarding claim 3
Rüddenklau further teaches wherein, in step c), a maximum energization data structure is provided, which, in the light intensity list, exclusively comprises light intensity entries (See page 76-The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source k at full power in the discretized direction of the vertical angle and see fig 5)
Rüddenklau does not teach the light intensity list, exclusively comprises light intensity entries which exceed a preselected threshold light intensity, and the corresponding individual light source identification lists exclusively comprise identification entries of individual light sources whose light intensity entries exceed the preselected threshold light intensity.
In the related field of invention, Waldner teaches the light intensity list, exclusively comprises light intensity entries which exceed a preselected threshold light intensity, and the corresponding individual light source identification lists exclusively comprise identification entries of individual light sources whose light intensity entries exceed the preselected threshold light intensity. (see section IV Waldner)
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Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Headlamps system for Night Driving Simulation as disclosed by Rüddenklau to include the light intensity list, exclusively comprises light intensity entries which exceed a preselected threshold light intensity, and the corresponding individual light source identification lists exclusively comprise identification entries of individual light sources whose light intensity entries exceed the preselected threshold light intensity as taught by Waldner in the system of Rüddenklau for using the complete real headlight system in a virtual testing scenario. With the Hardware-in-the-Loop simulation the engineer can evaluate real headlights in predefined and repeatable scenarios at any time in the lab. The virtual test scenarios can be reproductions form real test drives or worst-case analysis for specialized applications. In the Hardware-in-the-Loop test the real headlight can be exposure to heat, cold or water to evaluate the effects of environmental conditions. By using the presented Hardware-in-the-Loop simulation the duration and number of necessary night test drives can be reduced. Also, imperfections and faults can be found faster and earlier in the development process. The simulation calculates the light distribution in the virtual world from the intensities under consideration of the actual driving dynamics. (see Introduction, Waldner)
Regarding claim 4
Rüddenklau further teaches wherein the method additionally comprises, after step c2.1), the following step: determining the light intensity…on the coordinate; (See page 76-The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source k at full power in the discretized direction of the vertical angle and see fig 5)
Rüddenklau does not teach determining whether the light intensity of the maximum energization individual light distribution on the coordinate exceeds the preselected threshold light intensity.
In the related field of invention, Waldner teaches whether the light intensity of the maximum energization individual light distribution on the coordinate exceeds the preselected threshold light intensity. (see section IV Waldner)
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Rüddenklau further teaches performing steps c2.2) through c2.4) for this coordinate (see claim 2-Rüddenklau) based on the threshold light intensity being exceeded.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Headlamps system for Night Driving Simulation as disclosed by Rüddenklau to include whether the light intensity of the maximum energization individual light distribution on the coordinate exceeds the preselected threshold light intensity as taught by Waldner in the system of Rüddenklau for using the complete real headlight system in a virtual testing scenario. With the Hardware-in-the-Loop simulation the engineer can evaluate real headlights in predefined and repeatable scenarios at any time in the lab. The virtual test scenarios can be reproductions form real test drives or worst-case analysis for specialized applications. In the Hardware-in-the-Loop test the real headlight can be exposure to heat, cold or water to evaluate the effects of environmental conditions. By using the presented Hardware-in-the-Loop simulation the duration and number of necessary night test drives can be reduced. Also, imperfections and faults can be found faster and earlier in the development process. The simulation calculates the light distribution in the virtual world from the intensities under consideration of the actual driving dynamics. (see Introduction, Waldner)
Regarding claim 5
Rüddenklau does not teach wherein the method additionally comprises step b2) of determining a compressed maximum energization individual light distribution from the maximum energization individual light distribution; wherein the compressed maximum energization individual light distribution represents at least the light intensity of the individual light source in a coordinate region that is irradiated by the individual light source at maximum energization in such a way that the light intensity exceeds a second preselected threshold light intensity or a threshold light intensity based upon a preselected percentage threshold value.
However, Waldner further teaches wherein the method additionally comprises step b2) of determining a compressed maximum energization individual light distribution from the maximum energization individual light distribution; wherein the compressed maximum energization individual light distribution represents at least the light intensity of the individual light source in a coordinate region that is irradiated by the individual light source at maximum energization in such a way that the light intensity exceeds a second preselected threshold light intensity or a threshold light intensity based upon a preselected percentage threshold value, (see section IV-The camera adjustment is a multi-step progress, which requires the adjustment of multiple parameters in the correct order. The basic idea of the adjustment process is projecting light distributions with known intensity values on the wall. Then using the knowledge about the true Iv,max and Iv to calculate the camera parameters for an optimal I for (3). The chosen Rüddenklau light distribution determinate ~Iv,max so that the goal of the following image process is calculating the optimal relative distribution I from the image.)
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and
Rüddenklau further teaches wherein, in step c), the maximum energization data structure is determined taking into account all the compressed maximum energization individual light distributions. (See Rüddenklau page 76-Once both, the individual light distributions and the temporary intensity list, are available, the total light distribution can be calculated. This can be achieved by adding the individual light distributions weighted by the relative current values)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Headlamps system for Night Driving Simulation as disclosed by Rüddenklau to include wherein the method additionally comprises step b2) of determining a compressed maximum energization individual light distribution from the maximum energization individual light distribution; wherein the compressed maximum energization individual light distribution represents at least the light intensity of the individual light source in a coordinate region that is irradiated by the individual light source at maximum energization in such a way that the light intensity exceeds a second preselected threshold light intensity or a threshold light intensity based upon a preselected percentage threshold value as taught by Waldner in the system of Rüddenklau for using the complete real headlight system in a virtual testing scenario. With the Hardware-in-the-Loop simulation the engineer can evaluate real headlights in predefined and repeatable scenarios at any time in the lab. The virtual test scenarios can be reproductions form real test drives or worst-case analysis for specialized applications. In the Hardware-in-the-Loop test the real headlight can be exposure to heat, cold or water to evaluate the effects of environmental conditions. By using the presented Hardware-in-the-Loop simulation the duration and number of necessary night test drives can be reduced. Also, imperfections and faults can be found faster and earlier in the development process. The simulation calculates the light distribution in the virtual world from the intensities under consideration of the actual driving dynamics. (see Introduction, Waldner)
Regarding claim 6
Rüddenklau does not teach wherein the compressed maximum energization individual light distribution is determined by an edge detection algorithm.
However, Waldner further teaches wherein the compressed maximum energization individual light distribution is determined by an edge detection algorithm; (see section IV.D-The variance of the Laplacian is the chosen metric for this paper. With the Laplace-Filter L the optimization strategy is maximizing the variance of the second derivative of the image which represents the sharpness of the edges. The light distribution of headlights has soft edges compared to ordinary pictures, so finding the optimal focus point with an autofocus algorithm can be difficult. Changing the Rüddenklau light distribution to a stripe pattern with full or no power sharps the edges of the pixels and makes the optimum more unique. See Section IV.F)
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or wherein the determination of the compressed maximum energization individual light distribution comprises determining an effectively illuminated, rectangular coordinate region by the following steps:
receiving by the controller a scattered light-reduced maximum energization individual light distribution by reducing a scattered light component in the maximum energization individual light distribution;
determining a maximum light intensity and a coordinate having the maximum light intensity in the scattered light-reduced maximum energization individual light distribution;
determining the threshold light intensity taking into account the maximum light intensity and the preselected percentage threshold value; and
determining the effectively illuminated, rectangular coordinate region, taking into account the scattered light-reduced maximum energization individual light distribution, the coordinate having the maximum light intensity, and the threshold light intensity.
Examiner note: Under the BRI, claim 6 contains “or” that creates alternative implementations of step. Therefore, for step compressed maximum energization individual light distribution is determined by an edge detection algorithm is performed, it will meet the claim requirement. In the rejection, Examiner consider the edge detection algorithm embodiment for prior art rejection to meet claim 6. The additional steps are not required if the edge detection embodiment is taught. IN Waldner, Edges are detected using Laplacian operator and non-illuminated regions are removed via thresholding, thus Waldner teaches determining a compressed light distribution based on edge detection algorithm.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Headlamps system for Night Driving Simulation as disclosed by Rüddenklau to include wherein the compressed maximum energization individual light distribution is determined by an edge detection algorithm as taught by Waldner in the system of Rüddenklau for using the complete real headlight system in a virtual testing scenario. With the Hardware-in-the-Loop simulation the engineer can evaluate real headlights in predefined and repeatable scenarios at any time in the lab. The virtual test scenarios can be reproductions form real test drives or worst-case analysis for specialized applications. In the Hardware-in-the-Loop test the real headlight can be exposure to heat, cold or water to evaluate the effects of environmental conditions. By using the presented Hardware-in-the-Loop simulation the duration and number of necessary night test drives can be reduced. Also, imperfections and faults can be found faster and earlier in the development process. The simulation calculates the light distribution in the virtual world from the intensities under consideration of the actual driving dynamics. (see Introduction, Waldner)
8. Claim(s) 7-9 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rüddenklau et al. ("Real-Time Lighting of High-Definition Headlamps for Night Driving Simulation." International Journal on Advances in Systems and Measurements 12.3 & 4 (2019): 72-88) in view of Olsson et al. ("Clustered deferred and forward shading." Proceedings of the Fourth ACM SIGGRAPH/Eurographics Conference on High-Performance Graphics. 2012.)
Regarding claim 7
Rüddenklau further teaches wherein the method additionally comprises, after step d), the following steps:
d1) creating a target coordinates buffer from the target coordinates list, (see page 76-Adiscretized light distribution can be interpreted as a matrix. (See page 78 and fig 8-More precisely, the render target of the Cookie Combiner-Shader is a texture Tcomb with the same type and dimensions as the textures of the individual light distributions - a scalar floating-point texture with 900x900 texels. See page 79-80- The other parameter represents the relative intensity ik with which this light source is currently operated. Its code is executed for each texel of the render target Tcomb in parallel (see lower area of Figure 8), whereby the individual threads can be distinguished by further inherent parameters u and v constituting the normalized coordinates of the thread specific texel of the render target. Their common render target is the light buffer, visualized in the lower area of Figure 10)
a light intensity buffer from all the light intensity lists, (see page 76-The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source. See page 79-80- In the first step within processing, the shader reads the light intensity value tuv of the given individual light texture Tk at position (u; v) corresponding to the texel to be written to in the render target (line 1). Their common render target is the light buffer, visualized in the lower area of Figure 10)
wherein the target coordinates buffer contains a number of ZK elements which corresponds to the number of target coordinates entries of the target coordinates list, (see page 76-Adiscretized light distribution can be interpreted as a matrix. The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source. See page 78 and fig 8-More precisely, the render target of the Cookie Combiner-Shader is a texture Tcomb with the same type and dimensions as the textures of the individual light distributions - a scalar floating-point texture with 900x900 texels. See page 80- Their common render target is the light buffer, visualized in the lower area of Figure 10)
d2) storing, by the controller, the target coordinates buffer, the light intensity buffer, and the individual light source identification buffer. (see page 86 and table I-The results discussed below were recorded on a mobile PC, whose specification can be found in Table I.)
Rüddenklau does not teach an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure and the target coordinates buffer comprises a starting point and a length specification for each ZK element.
In the related field of invention, Olsson teaches an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure, (see page 6-In the sorting approach, we explicitly store this index for each pixel. This is achieved by tracking Rüddenklaus back to the originating pixel, and, when the unique cluster list is established, storing the index to the correct pixel in a full screen buffer.)
and the target coordinates buffer comprises a starting point and a length specification for each ZK element; (see section 3.4-For Tiled Shading, a simple 2D lookup, based on the screen-space coordinates, is sufficient to retrieve light-list offset and count. When using page tables, after the unique clusters are found, we store the cluster index back to the physical memory location used to store the cluster key earlier)
and
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Headlamps system for Night Driving Simulation as disclosed by Rüddenklau to include an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure and the target coordinates buffer comprises a starting point and a length specification for each ZK element as taught by Olsson in the system of Rüddenklau in order to investigate the Clustered Shading. Clustered Shading enables using normal information to perform per-cluster back-face culling of lights, again reducing the number of lighting computations. Clustered Shading not only outperforms tiled shading in many scenes, but also exhibits better worst-case behavior under tricky conditions (e.g. when looking at high-frequency geometry with large discontinuities in depth). Additionally, Clustered Shading enables real-time scenes with two to three orders of magnitudes more lights than previously feasible (up to around one million light sources). (see Abstract, Olsson)
Regarding claim 8
Rüddenklau further teaches wherein the method additionally comprises, after step d), the following steps:
e1) creating a target coordinates buffer from the target coordinates list, (see page 76-Adiscretized light distribution can be interpreted as a matrix. (See page 78 and fig 8-More precisely, the render target of the Cookie Combiner-Shader is a texture Tcomb with the same type and dimensions as the textures of the individual light distributions - a scalar floating-point texture with 900x900 texels. See page 79-80- The other parameter represents the relative intensity ik with which this light source is currently operated. Its code is executed for each texel of the render target Tcomb in parallel (see lower area of Figure 8), whereby the individual threads can be distinguished by further inherent parameters u and v constituting the normalized coordinates of the thread specific texel of the render target. Their common render target is the light buffer, visualized in the lower area of Figure 10)
a light intensity buffer from all the light intensity lists, (see page 76-The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source. See page 79-80- In the first step within processing, the shader reads the light intensity value tuv of the given individual light texture Tk at position (u; v) corresponding to the texel to be written to in the render target (line 1). Their common render target is the light buffer, visualized in the lower area of Figure 10)
wherein the target coordinates buffer contains a number of ZK elements which corresponds to the number of target coordinates entries of the target coordinates list, (see page 76-Adiscretized light distribution can be interpreted as a matrix. The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source. See page 78 and fig 8-More precisely, the render target of the Cookie Combiner-Shader is a texture Tcomb with the same type and dimensions as the textures of the individual light distributions - a scalar floating-point texture with 900x900 texels. See page 80- Their common render target is the light buffer, visualized in the lower area of Figure 10)
e2) transmitting the target coordinates buffer, the light intensity buffer, and the individual light source identification buffer to a graphics card of the controller; (see page 78- Once a way has been found to digitally map luminous intensity distributions to a graphics card compatible manner, the next step is to determine the total light distribution from the individual ones see page 86- The analysis in the profiler shows that combining the 95 floating point textures on the CPU requires an average of 0.45ms (min: 0.27ms, max: 0.64ms). With cookie combining, however, the CPU acts primarily as the client of the GPU. It instructs the graphics card to execute the Cookie Combiner shader by creating draw calls and defines the relevant context information, such as the render target or the current individual light distribution. See fig 8)
e3) creating an energization value buffer from the relative energization values; (see page 86-All relative current values are randomly selected between 0% and 100% for each calculation. See fig 8 –(weighting ik))
e4) transmitting the energization value buffer to the graphics card of the controller; (see page 86- The analysis in the profiler shows that combining the 95 floating point textures on the CPU requires an average of 0.45ms (min: 0.27ms, max: 0.64ms). With cookie combining, however, the CPU acts primarily as the client of the GPU. It instructs the graphics card to execute the Cookie Combiner shader by creating draw calls and defines the relevant context information, such as the render target or the current individual light distribution. See fig 8) and
e5) determining the total light distribution by using the graphics card of the controller, taking into account the target coordinates buffer, the light intensity buffer, the individual light source identification buffer, and the energization value buffer. (SEE PAGE 79-the Cookie Combiner is applied to the target texture repeatedly with iterating through all individual light sources by changing the parameters Tk and ik. The rendering is done with additive blending (see Figures 8 and 9), After applying the Cookie Combiner to all individual light sources k = 1; : : : ;K, the render target Tcomb contains the total luminous intensity distribution. See page 86- So it is not surprising that the GPU has a significantly higher average calculation time of 4.61ms (min: 4.44ms, max: 4.73ms).)
Rüddenklau does not teach an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure and the target coordinates buffer comprises a starting point and a length specification for each ZK element.
In the related field of invention, Olsson teaches an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure, (see page 6-In the sorting approach, we explicitly store this index for each pixel. This is achieved by tracking Rüddenklaus back to the originating pixel, and, when the unique cluster list is established, storing the index to the correct pixel in a full screen buffer.)
and the target coordinates buffer comprises a starting point and a length specification for each ZK element; (see section 3.4-For Tiled Shading, a simple 2D lookup, based on the screen-space coordinates, is sufficient to retrieve light-list offset and count. When using page tables, after the unique clusters are found, we store the cluster index back to the physical memory location used to store the cluster key earlier)
and
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Headlamps system for Night Driving Simulation as disclosed by Rüddenklau to include an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure and the target coordinates buffer comprises a starting point and a length specification for each ZK element as taught by Olsson in the system of Rüddenklau in order to investigate the Clustered Shading. Clustered Shading enables using normal information to perform per-cluster back-face culling of lights, again reducing the number of lighting computations. Clustered Shading not only outperforms tiled shading in many scenes, but also exhibits better worst-case behavior under tricky conditions (e.g. when looking at high-frequency geometry with large discontinuities in depth). Additionally, Clustered Shading enables real-time scenes with two to three orders of magnitudes more lights than previously feasible (up to around one million light sources). (see Abstract, Olsson)
Regarding claim 9
Rüddenklau further teaches wherein, in step e5), a computer shader having shading units is used, wherein each shader unit processes one ZK element in isolation, and/or wherein the execution strings of the computer shader run in parallel on several shader units of the graphics card. (See page 78-Once a way has been found to digitally map luminous intensity distributions to a graphics card compatible manner, the next step is to determine the total light distribution from the individual ones. The result can then be used to adjust the light intensity in the lighting pass, more precisely in the Headlight-Shader executed in it (see Section III-C), depending on the direction. Vividly, this realization is comparable to a dynamic transparency film, by which a homogeneous light source is filtered to produce the desired radiation characteristic. Texturing of light sources to vary the luminous intensity indifferent beam directions is already established. Such light textures are called cookies, explaining the name of the Cookie Combiner-Shader. Its task is to combine the textures of the individual light distributions into a total light distribution texture according to Equation (4). Figure 9 illustrates the data flow of the combining procedure on a mathematical level. The implementation of this calculation as a shader enables the highly parallel execution on the graphics card, which is necessary to fulfill the real-time requirements.)
Regarding claim 14
Rüddenklau further teaches wherein a one-time performance of steps a) through c) (See page 76 and fig 5-In concrete terms, each luminous intensity distribution is converted into a texture, as illustrated in the upper left area of Figure 5. See page 74-The individual light distributions are measured with running the corresponding LEDs at full power. See page 79-After completion of the shader operations for all texels, the target texture contains the contribution of the light source k within the total light distribution, whereby a single component of the sum in the data flow visualized by Figure 9 is mapped. In order to obtain the complete light distribution of the headlamp, all texels of the render target Tcomb are first initialized with 0. Then the Cookie Combiner is applied to the target texture repeatedly with iterating through all individual light sources by changing the parameters Tk and ik. The rendering is done with additive blending (see Figures 8 and 9) so the previous values in the render target are not overwritten by the returns of the shader but added to it)
is followed by a one-time performance of steps e1) or a one-time performance of steps e1′) and e2), e1) creating a target coordinates buffer from the target coordinates list, (see page 76-Adiscretized light distribution can be interpreted as a matrix. (See page 78 and fig 8-More precisely, the render target of the Cookie Combiner-Shader is a texture Tcomb with the same type and dimensions as the textures of the individual light distributions - a scalar floating-point texture with 900x900 texels. See page 79-80- The other parameter represents the relative intensity ik with which this light source is currently operated. Its code is executed for each texel of the render target Tcomb in parallel (see lower area of Figure 8), whereby the individual threads can be distinguished by further inherent parameters u and v constituting the normalized coordinates of the thread specific texel of the render target. Their common render target is the light buffer, visualized in the lower area of Figure 10)
a light intensity buffer from all the light intensity lists, (see page 76-The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source. See page 79-80- In the first step within processing, the shader reads the light intensity value tuv of the given individual light texture Tk at position (u; v) corresponding to the texel to be written to in the render target (line 1). Their common render target is the light buffer, visualized in the lower area of Figure 10)
wherein the target coordinates buffer contains a number of ZK elements which corresponds to the number of target coordinates entries of the target coordinates list, (see page 76-Adiscretized light distribution can be interpreted as a matrix. The entry lk(m; n) of row m and column n of the Lk matrix now contains the luminous intensity of the light source. See page 78 and fig 8-More precisely, the render target of the Cookie Combiner-Shader is a texture Tcomb with the same type and dimensions as the textures of the individual light distributions - a scalar floating-point texture with 900x900 texels. See page 80- Their common render target is the light buffer, visualized in the lower area of Figure 10)
and repeated, successive performances of steps e3) through e5). e3) creating an energization value buffer from the provided relative energization values; (see page 86-All relative current values are randomly selected between 0% and 100% for each calculation. See fig 8 –(weighting ik))
e4) transmitting the energization value buffer to the graphics card of the controller; (see page 86- The analysis in the profiler shows that combining the 95 floating point textures on the CPU requires an average of 0.45ms (min: 0.27ms, max: 0.64ms). With cookie combining, however, the CPU acts primarily as the client of the GPU. It instructs the graphics card to execute the Cookie Combiner shader by creating draw calls and defines the relevant context information, such as the render target or the current individual light distribution. See fig 8) and
e5) determining the total light distribution by using the graphics card of the controller, taking into account the target coordinates buffer, the light intensity buffer, the individual light source identification buffer, and the energization value buffer. (SEE PAGE 79-the Cookie Combiner is applied to the target texture repeatedly with iterating through all individual light sources by changing the parameters Tk and ik. The rendering is done with additive blending (see Figures 8 and 9), After applying the Cookie Combiner to all individual light sources k = 1; : : : ;K, the render target Tcomb contains the total luminous intensity distribution. See page 86- So it is not surprising that the GPU has a significantly higher average calculation time of 4.61ms (min: 4.44ms, max: 4.73ms).)
Rüddenklau does not teach an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure and the target coordinates buffer comprises a starting point and a length specification for each ZK element.
In the related field of invention, Olsson teaches an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure, (see page 6-In the sorting approach, we explicitly store this index for each pixel. This is achieved by tracking Rüddenklaus back to the originating pixel, and, when the unique cluster list is established, storing the index to the correct pixel in a full screen buffer.)
and the target coordinates buffer comprises a starting point and a length specification for each ZK element; (see section 3.4-For Tiled Shading, a simple 2D lookup, based on the screen-space coordinates, is sufficient to retrieve light-list offset and count. When using page tables, after the unique clusters are found, we store the cluster index back to the physical memory location used to store the cluster key earlier)
and
Examiner note: Under the BRI, claim 14 contains “or” that creates alternative implementations of step (e). Therefore, for step (e) it is satisfied if either steps e1) is performed or steps e1′) and e2), are performed. In the rejection, Examiner consider the e1 buffer creation embodiment for prior art rejection to meet claim 14. The additional steps e11 and e2 are not required if the e1 embodiment is taught.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Headlamps system for Night Driving Simulation as disclosed by Rüddenklau to include an individual light source identification buffer from all the individual light source identification lists of the maximum energization data structure and the target coordinates buffer comprises a starting point and a length specification for each ZK element as taught by Olsson in the system of Rüddenklau in order to investigate the Clustered Shading. Clustered Shading enables using normal information to perform per-cluster back-face culling of lights, again reducing the number of lighting computations. Clustered Shading not only outperforms tiled shading in many scenes, but also exhibits better worst-case behavior under tricky conditions (e.g. when looking at high-frequency geometry with large discontinuities in depth). Additionally, Clustered Shading enables real-time scenes with two to three orders of magnitudes more lights than previously feasible (up to around one million light sources). (see Abstract, Olsson)
Conclusion
10. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Neukam et al. US20210162913A1
i. Discussing the method for lighting the vehicle surroundings of the motor vehicle, control devices for controlling the pixel lamp of the motor vehicle.
Funk et al. US20190202343A1
ii. Discussing the method of motor vehicle having at least one headlight for illuminating the surroundings of the motor vehicle and a control device for controlling the headlight, wherein the headlight comprises a plurality of lighting segments that are arranged in the manner of a matrix and that can be actuated separately by the control device for providing a lighting brightness that can be predefined separately for the individual lighting segments, wherein the control parameter predefining the specific lighting brightness for each of the lighting segments can be calculated by the control device in at least one computing step as a function of input parameters that can be provided by at least one vehicle device.
All claims 1-20 are rejected.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
12. Any inquiry concerning this communication or earlier communications from the examiner should be directed to PURSOTTAM GIRI whose telephone number is (469)295-9101. The examiner can normally be reached 7:30-5:30 PM, Monday to Friday.
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/PURSOTTAM GIRI/
Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186
