Detailed Office Action
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This is a non-final Office Action on the merits. Claims 1-10 are currently pending and are addressed below.
Priority
Acknowledgment is made of applicant's claim priority for JP2023-200746 filed November 28th, 2023.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 11/19/2024 is being considered by the examiner.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier.
Such claim limitation(s) are:
“a first processing device” in Claim 1 is being interpreted as a generic processor
“a second processing device” in Claim 1 is being interpreted as a generic processor
“a first control device” in Claim 2 is being interpreted as a generic processor
“a second control device” in Claim 2 is being interpreted as a generic processor
“a third control device” in Claim 2 is being interpreted as a generic processor
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
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 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The analysis of the claims’ subject matter eligibility will follow the 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50-57 (January 7, 2019) (“2019 PEG”).
101 Analysis - With respect to Claim 1
Claim 1, 9, 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis - Step 1:
Claim 1 is directed towards a device which is directed to the statutory category of a machine. Claim 9 is directed towards a non-transitory computer readable medium which is directed to the statutory category of a manufacture. Claim 10 is directed towards a method which is directed to the statutory category of a process. Therefore Claims 1, 9, and 10 are within at least one of the four statutory categories.
101 Analysis- Step 2A Prong One:
Regarding Prong One of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental process.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection.
Claim 1 recites, inter alai:
“A vehicle control device comprising:
a first processing device that generates an output signal using only a machine learning-trained classifier;
a second processing device that has lower power consumption than the first processing device and generates an output signal without using a machine learning-trained classifier; and
a processor configured to decide a processing ratio between a portion processed by the first processing device and a portion processed by the second processing device, based on at least one information from among vehicle information representing a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing terrain including a current location of the vehicle.”
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind.
For example, “deciding” in the context of this claim, encompasses a person looking at available data and forming a simple judgement (determination, analysis, comparison, etc.) either manually or using a pen and paper. Accordingly, the claim recites at least one abstract idea. The examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
As drafted, the above claims, under their broadest reasonable interpretation, cover mental processes performed in the human mind (including an observation, evaluation, judgement, opinion), that are merely completed via generic computer components. Accordingly, the claims recite an abstract idea.
Step 2A Prong Two Analysis:
Regarding Prong Two of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract idea into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application”.
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
Claim 1 recites, inter alai:
“A vehicle control device comprising:
a first processing device that generates an output signal using only a machine learning-trained classifier;
a second processing device that has lower power consumption than the first processing device and generates an output signal without using a machine learning-trained classifier; and
a processor configured to decide a processing ratio between a portion processed by the first processing device and a portion processed by the second processing device, based on at least one information from among vehicle information representing a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing terrain including a current location of the vehicle.”
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitation of “a first processing device that generates an output signal…” and “a second processing device that has lower power consumption than the first processing device and generates an output signal…”, this limitation merely describes how to generally “apply” the otherwise mental judgements in a generic or general purpose vehicle control environment. See Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). The device(s) and processor(s) are recited at a high level of generality and merely automates the steps.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
Step 2B Analysis:
The claims do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using generic computer components to perform the abstract idea amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
Regarding dependent claims 2-8, no claim further adds a limitation that introduces any practical applications to the claimed invention, the dependent claims merely add more mental process, mathematical concepts, and post-solution activities and are thus not patent eligible.
Therefore, Claims 1-10 are ineligible under 35 USC §101.
Claim Rejections - 35 USC § 103
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.
Claims 1-3, 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al (CN 115543583 A) in view of Li (CN 115827244 A). Hereafter referred to as Zhang and Li respectively.
Regarding Claim 1, Zhang teaches a vehicle control device (see at least Zhang [English Translation pg.5 para.7] The task allocation method according to the embodiment of the present disclosure, the task processing method can be executed by the terminal device...the terminal device can be a...vehicle device)
a first processing device that generates an output signal using only a machine learning-trained classifier (see at least Zhang [English Translation pg.7 para.2, pg.6 para.7] the processing architecture 300 comprises…a special processor 322…the task to be processed comprises a general task and a special task, wherein the general task is the task of the general type, generally corresponding to the general program, the special task refers to the task of some special field (e.g., task in the field of neural network))
a second processing device that has lower power consumption than the first processing device and generates an output signal without using a machine learning-trained classifier (see at least Zhang [English Translation pg.7 para.2, pg.6 para.7] the processing architecture 300 comprises...a general processor 312…the task to be processed comprises a general task and a special task, wherein the general task is the task of the general type, generally corresponding to the general program)
a processor configured to decide a processing ratio between a portion processed by the first processing device and a portion processed by the second processing device (see at least Zhang [English Translation Abstract and pg.6 para.6-7] it is capable of considering the computing power of the cost, selecting proper compiling mode and processing mode for each task to be processed, so as to more reasonably use processing resource of two different processing mode...for a plurality of tasks to be processed, determining each task to be processed by the first cost corresponding to the general processing mode and the second cost corresponding to the special processing mode; according to the first cost and the second cost corresponding to each task to be processed...Furthermore, in general, the special program can only be run in the special processor, so the special task can only be executed by the special processor) The disclosure in Zhang teaches a control device that can allocate tasks between two processors, a general processor and a special processor, wherein the special processor utilizes neural network technology (which is analogous to using a machine learning trained classifier) and can perform special tasks that the general processor, without the neural network technology, cannot. The system in Zhang will allocate the tasks between the processors depending on the task, which is analogous to deciding a processing ratio. Zhang further discloses such a system can be used for a vehicle.
However, while Zhang teaches a system that can allocate tasks (decide processing ratio) between a generic processor and a neural network processor for a vehicle based on information regarding a particular task, it does not explicitly teach wherein the information represents a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing terrain including a current location of the vehicle.
Li, in the same field as the endeavor, teaches wherein the deciding of the processing ratio is based on at least one information from among vehicle information representing a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing terrain including a current location of the vehicle (see at least Li [English Translation Abstract and pg.2 para.3, pg.3 para.3] the application embodiment provides a vehicle processor resource allocation method, the vehicle comprises a processor resource pool, the processor resource pool comprises a plurality of shared processor…the application can dynamically allocate different number of processor resources to the ADAS and IVI system according to the using state of the vehicle, it not only can avoid the waste of the processor computing power reduce the production cost of the vehicle, but also can effectively ensure the normal use of the IVI system and the ADAS in the complex use scene…the use state of the vehicle comprises a parking state and a driving state).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in Zhang to contain a system wherein the deciding of the processing ratio is based on at least one information from among vehicle information representing a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing terrain including a current location of the vehicle with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of reducing the waste of computing power and production cost as discussed in Li (see at least Li [English Translation Abstract] can avoid the waste of the processor computing power reduce the production cost of the vehicle).
Regarding Claim 2, Zhang in view of Li teaches all limitations of Claim 1 as set forth above. Zhang further teaches a plurality of the first processing devices and a plurality of the second processing devices (see at least Zhang [English Translation pg.19 para.1] one physical component may have a plurality of functions, or one function or step may be performed by a plurality of physical components. Some physical components or all physical components may be implemented as a processor)
However, Zhang does not explicitly teach a first control device that has one of the first processing devices and one of the second processing devices; a second control device that has higher power consumption than the first control device and generates an output signal using only another of the first processing devices; a third control device that has lower power consumption than the first control device and generates an output signal using only another of the second processing devices
and wherein the processor is further configured to select a selected control device for control of the vehicle from among the first control device, second control device and third control device based on the decided processing ratio.
Li, in the same field as the endeavor, teaches a first control device that has one of the first processing devices and one of the second processing devices; a second control device that has higher power consumption than the first control device and generates an output signal using only another of the first processing devices; a third control device that has lower power consumption than the first control device and generates an output signal using only another of the second processing devices (see at least Li [English Translation pg.2 para.10-14] the processor resource pool further comprises a multi-path selection switch, the multi-path selection switch comprises a first port, a second port and a plurality of third ports, the first port is connected with the ADAS, the second port is connected with the IVI system, each of the third port is connected with one of the shared processor;...selecting the M shared processors to be allocated to the ADAS in the processor resource pool, and selecting the N shared processors to be allocated to the IVI system in the shared processor remaining in the processor resource pool, comprising: controlling the multi-path selection switch, conducting the first port and the M third ports in the plurality of third ports, and conducting the second port and the N third ports in the remaining third port) The disclosure in Li describes allocating processing resources to different combinations of different processing devices, in view of Zhang’s disclosed first and second processing devices, any combination of processing devices composed of the first and second processing devices would be obvious to anyone of ordinary skill in the art.
and wherein the processor is further configured to select a selected control device for control of the vehicle from among the first control device, second control device and third control device based on the decided processing ratio (see at least Li [English Translation Abstract and pg.2 para.2, pg.3 para.3, pg.9 para.1-3] The application claims a processor resource distribution method and device of vehicle, relating to the technical field of intelligent automobile, the vehicle comprises a processor resource pool, the processor resource pool comprises a plurality of shared processors…The application can dynamically allocate different number of processor resources to the ADAS and IVI system according to the using state of the vehicle...The allocation module 403 is specifically configured to: controlling the multi-path selection switch, conducting the first port and the M third ports in the plurality of third ports, and conducting the second port and the N third ports in the remaining third port...according to the current use state of the vehicle, and a predetermined processor allocation scheme corresponding to each use state, determining the number of processors needed by the ADAS and the IVI system).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in Zhang to contain a first control device that has one of the first processing devices and one of the second processing devices; a second control device that has higher power consumption than the first control device and generates an output signal using only another of the first processing devices; a third control device that has lower power consumption than the first control device and generates an output signal using only another of the second processing devices and wherein the processor is further configured to select a selected control device for control of the vehicle from among the first control device, second control device and third control device based on the decided processing ratio with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of reducing the waste of computing power and production cost as discussed in Li (see at least Li [English Translation Abstract] can avoid the waste of the processor computing power reduce the production cost of the vehicle).
Regarding Claim 3, Zhang in view of Li teaches all limitations of Claim 1 as set forth above. However, Zhang does not explicitly teach wherein the vehicle information includes degree of operation of the vehicle, and the processor is further configured to decide the processing ratio according to the degree of operation of the vehicle.
Li, in the same field as the endeavor, teaches wherein the vehicle information includes degree of operation of the vehicle, and the processor is further configured to decide the processing ratio according to the degree of operation of the vehicle (see at least Li [English Translation pg.9 para.2-3] The determining module 402 is specifically used for: according to the current use state of the vehicle, and a predetermined processor allocation scheme corresponding to each use state, determining the number of processors needed by the ADAS and the IVI system).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in Zhang to contain a system for wherein the vehicle information includes degree of operation of the vehicle, and the processor is further configured to decide the processing ratio according to the degree of operation of the vehicle with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of reducing the waste of computing power and production cost as discussed in Li (see at least Li [English Translation Abstract] can avoid the waste of the processor computing power reduce the production cost of the vehicle).
Regarding Claim 9, Zhang teaches a computer-readable, non-transitory storage medium storing a computer program for vehicle control, which causes a processor to execute a process (see at least Zhang [English Translation pg.18 para.11] The embodiment of the invention further claims a computer program product, comprising a computer readable code, or a non-volatile computer readable storage medium bearing computer readable code, when the computer readable code in the processor of the electronic device, The processor in the electronic device executes the task allocation method or task processing method)
the process comprising:
deciding a processing ratio between a portion processed by a first processing device that generates an output signal using only a machine learning-trained classifier, and a portion processed by a second processing device that has lower power consumption than the first processing device and generates an output signal without using a machine learning-trained classifier (see at least Zhang [English Translation Abstract and pg.7 para.2, pg.6 para.6-7] the processing architecture 300 comprises…a general processor 312…a special processor 322…the task to be processed comprises a general task and a special task, wherein the general task is the task of the general type, generally corresponding to the general program, the special task refers to the task of some special field (e.g., task in the field of neural network)… it is capable of considering the computing power of the cost, selecting proper compiling mode and processing mode for each task to be processed, so as to more reasonably use processing resource of two different processing mode...for a plurality of tasks to be processed, determining each task to be processed by the first cost corresponding to the general processing mode and the second cost corresponding to the special processing mode; according to the first cost and the second cost corresponding to each task to be processed...Furthermore, in general, the special program can only be run in the special processor, so the special task can only be executed by the special processor) The disclosure in Zhang teaches a control device that can allocate tasks between two processors, a general processor and a special processor, wherein the special processor utilizes neural network technology (which is analogous to using a machine learning trained classifier) and can perform special tasks that the general processor, without the neural network technology, cannot. The system in Zhang will allocate the tasks between the processors depending on the task, which is analogous to deciding a processing ratio. Zhang further discloses such a system can be used for a vehicle.
However, while Zhang teaches a system that can allocate tasks (decide processing ratio) between a generic processor and a neural network processor for a vehicle based on information regarding a particular task, it does not explicitly teach wherein the information represents a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing terrain including a current location of the vehicle.
Li, in the same field as the endeavor, teaches wherein the deciding of the processing ratio is based on at least one information from among vehicle information representing a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing a terrain including a current location of the vehicle (see at least Li [English Translation Abstract and pg.2 para.2, pg.3 para.3] the application embodiment provides a vehicle processor resource allocation method, the vehicle comprises a processor resource pool, the processor resource pool comprises a plurality of shared processor…the application can dynamically allocate different number of processor resources to the ADAS and IVI system according to the using state of the vehicle, it not only can avoid the waste of the processor computing power reduce the production cost of the vehicle, but also can effectively ensure the normal use of the IVI system and the ADAS in the complex use scene…the use state of the vehicle comprises a parking state and a driving state).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in Zhang to contain a system wherein the deciding of the processing ratio is based on at least one information from among vehicle information representing a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing terrain including a current location of the vehicle with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of reducing the waste of computing power and production cost as discussed in Li (see at least Li [English Translation Abstract] can avoid the waste of the processor computing power reduce the production cost of the vehicle).
Regarding Claim 10, Zhang a method for controlling a vehicle carried out by a vehicle control device (see at least Zhang [English Translation pg.5 para.7] The task allocation method according to the embodiment of the present disclosure, the task processing method can be executed by the terminal device...the terminal device can be a...vehicle device)
and the method comprising:
deciding a processing ratio between a portion processed by a first processing device that generates an output signal using only a machine learning-trained classifier, and a portion processed by a second processing device that has lower power consumption than the first processing device and generates an output signal without using a machine learning-trained classifier (see at least Zhang [English Translation Abstract and pg.7 para.2, pg.6 para.6-7] the processing architecture 300 comprises…a general processor 312…a special processor 322…the task to be processed comprises a general task and a special task, wherein the general task is the task of the general type, generally corresponding to the general program, the special task refers to the task of some special field (e.g., task in the field of neural network)… it is capable of considering the computing power of the cost, selecting proper compiling mode and processing mode for each task to be processed, so as to more reasonably use processing resource of two different processing mode...for a plurality of tasks to be processed, determining each task to be processed by the first cost corresponding to the general processing mode and the second cost corresponding to the special processing mode; according to the first cost and the second cost corresponding to each task to be processed...Furthermore, in general, the special program can only be run in the special processor, so the special task can only be executed by the special processor) The disclosure in Zhang teaches a control device that can allocate tasks between two processors, a general processor and a special processor, wherein the special processor utilizes neural network technology (which is analogous to using a machine learning trained classifier) and can perform special tasks that the general processor, without the neural network technology, cannot. The system in Zhang will allocate the tasks between the processors depending on the task, which is analogous to deciding a processing ratio. Zhang further discloses such a system can be used for a vehicle.
However, while Zhang teaches a system that can allocate tasks (decide processing ratio) between a generic processor and a neural network processor for a vehicle based on information regarding a particular task, it does not explicitly teach wherein the information represents a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing terrain including a current location of the vehicle.
Li, in the same field as the endeavor, teaches wherein the deciding of the processing ratio is based on at least one information from among vehicle information representing a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing a terrain including a current location of the vehicle (see at least Li [English Translation Abstract and pg.2 para.3, pg.3 para.3] the application embodiment provides a vehicle processor resource allocation method, the vehicle comprises a processor resource pool, the processor resource pool comprises a plurality of shared processor…the application can dynamically allocate different number of processor resources to the ADAS and IVI system according to the using state of the vehicle, it not only can avoid the waste of the processor computing power reduce the production cost of the vehicle, but also can effectively ensure the normal use of the IVI system and the ADAS in the complex use scene…the use state of the vehicle comprises a parking state and a driving state).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in Zhang to contain a system wherein the deciding of the processing ratio is based on at least one information from among vehicle information representing a state of a vehicle, environment information representing surrounding environment of the vehicle, and terrain information representing terrain including a current location of the vehicle with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of reducing the waste of computing power and production cost as discussed in Li (see at least Li [English Translation Abstract] can avoid the waste of the processor computing power reduce the production cost of the vehicle).
Claims 4-6 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al (CN 115543583 A) in view of Li (CN 115827244 A) and Park et al (US 20210247762 A1). Hereafter referred to as Zhang, Li, and Park respectively.
Regarding Claim 4, Zhang in view of Li teaches all limitations of Claim 3 as set forth above. However, Zhang does not explicitly teach wherein the vehicle information includes speed of the vehicle, and the processor is further configured to decide the processing ratio so that the portion processed by the first processing device is greater than the portion processed by the second processing device when the speed of the vehicle is slow compared to when the speed of the vehicle is fast.
Park, in the same field as the endeavor, teaches wherein the vehicle information includes speed of the vehicle, and the processor is further configured to decide the processing ratio so that the portion processed by the first processing device is greater than the portion processed by the second processing device when the speed of the vehicle is slow compared to when the speed of the vehicle is fast (see at least Park [¶ 32, 36-37] External vehicle conditions that may be considered in various embodiments when allocating processing resources to applications may include a driving speed…the processor may allocate finite processing resources to each of a plurality of vehicle applications based on a determination of a priority of each vehicle application to safe vehicle operations in a moment-to-moment, context-determined manner based on internal and external vehicle conditions...Each of a plurality of vehicle applications may be assigned different safety-related priorities based on various vehicle conditions. For example, as driving speed increases, sensor polling rates, data analysis, safety decisions by the processor, information display adjustments, and the like may need to be performed or refreshed more frequently to maintain a threshold level of safety performance).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in Zhang to contain a system for wherein the vehicle information includes speed of the vehicle, and the processor is further configured to decide the processing ratio so that the portion processed by the first processing device is greater than the portion processed by the second processing device when the speed of the vehicle is slow compared to when the speed of the vehicle is fast with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of improving the safety of the vehicle when determining how to allocate computing resources as discussed in Park (see at least Park [¶ 44] Various embodiments improve the safety of vehicles by allocating finite computing resources to the plurality of vehicle applications according to the importance of the vehicle application to safe vehicle operations or impact on a driver's ability to perform one or more safety-related tasks in a particular situation or context).
Regarding Claim 5, Zhang in view of Li teaches all limitations of Claim 1 as set forth above. However, Zhang does not explicitly teach wherein the environment information includes complexity of the surrounding environment of the vehicle, and the processor is further configured to decide the processing ratio so that the portion processed by the first processing device is greater than the portion processed by the second processing device when the degree of complexity of the surrounding environment of the vehicle is high, compared to when the degree of complexity of the surrounding environment of the vehicle is low.
Park, in the same field as the endeavor, teaches wherein the environment information includes complexity of the surrounding environment of the vehicle, and the processor is further configured to decide the processing ratio so that the portion processed by the first processing device is greater than the portion processed by the second processing device when the degree of complexity of the surrounding environment of the vehicle is high, compared to when the degree of complexity of the surrounding environment of the vehicle is low (see at least Park [¶ 32, 36-37] External vehicle conditions that may be considered in various embodiments when allocating processing resources to applications may include...direction of motion of other objects such as vehicles, pedestrians, etc.; an anticipated or planned path of the vehicle; the presence or detection of road hazards, accidents, or other similar threatening conditions…the processor may allocate finite processing resources to each of a plurality of vehicle applications based on a determination of a priority of each vehicle application to safe vehicle operations in a moment-to-moment, context-determined manner based on internal and external vehicle conditions...Each of a plurality of vehicle applications may be assigned different safety-related priorities based on various vehicle conditions....External vehicle conditions that may be considered in various embodiments when allocating processing resources to applications may include...direction of motion of other objects such as vehicles, pedestrians, etc.; an anticipated or planned path of the vehicle; the presence or detection of road hazards, accidents, or other similar threatening conditions (For example, as driving speed increases, sensor polling rates, data analysis, safety decisions by the processor, information display adjustments, and the like may need to be performed or refreshed more frequently to maintain a threshold level of safety performance)) Per the example of increasing the allocation computing resources when vehicle speed increases, it would be obvious to anyone of ordinary skill in the art that the same is true when the complexity of the environment increases due to the disclosed road hazards and obstacles.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in Zhang to contain a system for wherein the terrain information includes degree of complexity of the terrain including the current location of the vehicle, and the processor is further configured to decide the processing ratio so that the portion processed by the first processing device is greater than the portion processed by the second processing device when the degree of complexity of the terrain including the current location of the vehicle is high, compared to when the degree of complexity of the terrain including the current location of the vehicle is low with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of improving the safety of the vehicle when determining how to allocate computing resources as discussed in Park (see at least Park [¶ 44] Various embodiments improve the safety of vehicles by allocating finite computing resources to the plurality of vehicle applications according to the importance of the vehicle application to safe vehicle operations or impact on a driver's ability to perform one or more safety-related tasks in a particular situation or context).
Regarding Claim 6, Zhang in view of Li teaches all limitations of Claim 1 as set forth above. However, Zhang does not explicitly teach wherein the terrain information includes degree of complexity of the terrain including the current location of the vehicle, and the processor is further configured to decide the processing ratio so that the portion processed by the first processing device is greater than the portion processed by the second processing device when the degree of complexity of the terrain including the current location of the vehicle is high, compared to when the degree of complexity of the terrain including the current location of the vehicle is low.
Park, in the same field as the endeavor, teaches wherein the terrain information includes degree of complexity of the terrain including the current location of the vehicle, and the processor is further configured to decide the processing ratio so that the portion processed by the first processing device is greater than the portion processed by the second processing device when the degree of complexity of the terrain including the current location of the vehicle is high, compared to when the degree of complexity of the terrain including the current location of the vehicle is low (see at least Park [¶ 32, 36-37, 61] External vehicle conditions that may be considered in various embodiments when allocating processing resources to applications may include...road conditions, ambient temperature, ambient humidity, and weather conditions...the presence or detection of road hazards, accidents, or other similar threatening conditions…the map fusion and arbitration vehicle application 208 may convert latitude and longitude information from GPS into locations within a surface map of roads contained in the HD map database…the processor may allocate finite processing resources to each of a plurality of vehicle applications based on a determination of a priority of each vehicle application to safe vehicle operations in a moment-to-moment, context-determined manner based on internal and external vehicle conditions...Each of a plurality of vehicle applications may be assigned different safety-related priorities based on various vehicle conditions....External vehicle conditions that may be considered in various embodiments when allocating processing resources to applications may include...road conditions, ambient temperature, ambient humidity, and weather conditions...the presence or detection of road hazards, accidents, or other similar threatening conditions (For example, as driving speed increases, sensor polling rates, data analysis, safety decisions by the processor, information display adjustments, and the like may need to be performed or refreshed more frequently to maintain a threshold level of safety performance)) Per the example of increasing the allocation computing resources when vehicle speed increases, it would be obvious to anyone of ordinary skill in the art that the same is true when the complexity of the terrain increases due to the disclosed road conditions and weather conditions.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in Zhang to contain a system for wherein the terrain information includes degree of complexity of the terrain including the current location of the vehicle, and the processor is further configured to decide the processing ratio so that the portion processed by the first processing device is greater than the portion processed by the second processing device when the degree of complexity of the terrain including the current location of the vehicle is high, compared to when the degree of complexity of the terrain including the current location of the vehicle is low with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of improving the safety of the vehicle when determining how to allocate computing resources as discussed in Park (see at least Park [¶ 44] Various embodiments improve the safety of vehicles by allocating finite computing resources to the plurality of vehicle applications according to the importance of the vehicle application to safe vehicle operations or impact on a driver's ability to perform one or more safety-related tasks in a particular situation or context).
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al (CN 115543583 A) in view of Li (CN 115827244 A), Noda et al (US 20220407821 A1), and Park et al (US 20210247762 A1). Hereafter referred to as Zhang, Li, Noda and Park respectively.
Regarding Claim 7, Zhang in view of Li teaches all limitations of Claim 2 as set forth above. However, Zhang does not explicitly teach wherein the processor is further configured to decide amount of information to be input to the selected control device that has been selected, based on at least one information from among the vehicle information, environment information and terrain information.
Noda, in the same field as the endeavor, teaches wherein the processor is further configured to decide amount of information to be input to the selected control device that has been selected, based on at least one information from among the vehicle information, environment information and terrain information (see at least Noda [Abstract and ¶ 37, 50] The process includes, calculating, in a case where a notification that a resource is increased is received from a first processing device in a group of processing devices at a previous stage of the processing device among the plurality of processing devices, a ratio of an amount of data received from the first processing device to a total amount of data received from each of the group of processing devices...The processing device 101 receives an increase notification from a first processing device in the processing device group at the previous stage of the processing device 101. The increase notification is a notification indicating that a resource has been increased. Increasing the resource of a processing device tends to improve the processing capacity of the processing device and increase the amount of data flowing from the processing device to a processing device at the subsequent stage....in the case of a connected car, it is possible to analyze a large amount of data collected from a vehicle such as speed and position and to feed risk information or the like back to the driver of the vehicle).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in Zhang to contain a system for wherein the processor is further configured to decide amount of information to be input to the selected control device that has been selected, based on at least one information from among the vehicle information, environment information and terrain information with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of improving the processing capabilities by adjusting the amount of data input to a processor as discussed in Noda (see at least Noda [¶ 37] Increasing the resource of a processing device tends to improve the processing capacity of the processing device and increase the amount of data flowing from the processing device to a processing device at the subsequent stage).
Regarding Claim 8, Zhang in view of Li and Noda teaches all limitations of Claim 7 as set forth above. However, Zhang does not explicitly teach wherein the amount of information includes number of sensors with which detected information is input to the selected control device, the resolution of image input to the selected control device, and detection frequency of a sensor with which detected information is input to the selected control device.
Park, in the same field as the endeavor, teaches wherein the amount of information includes number of sensors with which detected information is input to the selected control device, the resolution of image input to the selected control device, and detection frequency of a sensor with which detected information is input to the selected control device (see at least Park [37, 45, 66] as driving speed increases, sensor polling rates, data analysis, safety decisions by the processor, information display adjustments, and the like may need to be performed or refreshed more frequently to maintain a threshold level of safety performance. As another example, if the vehicle is traveling along a long straightaway or in light traffic conditions, a polling rate of lane detection sensors and/or vehicle proximity sensors may be reduced with minimal impact on driving safety…a vehicle 100 may include a control unit 140 and a plurality of sensors 102-138, including…cameras 122, 136…The plurality of sensors 102-138, disposed in or on the vehicle, may be used for various purposes, such as autonomous and semi-autonomous navigation and control, crash avoidance, position determination, etc., as well to provide sensor data regarding objects and people in or on the vehicle 100…state information may include…on board sensor resolution).
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to have modified the system set forth in wherein the amount of information includes number of sensors with which detected information is input to the selected control device, the resolution of image input to the selected control device, and detection frequency of a sensor with which detected information is input to the selected control device to contain a system for wherein the amount of information includes number of sensors with which detected information is input to the selected control device, the resolution of image input to the selected control device, and detection frequency of a sensor with which detected information is input to the selected control device with reasonable expectation of success. One of ordinary skill in the art would have been motivated to make such a modification for benefit of including sensor data that is commonly used in vehicle control operations.
Conclusion
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/JOSEPH ANDERSON YANOSKA/Examiner, Art Unit 3664
/RACHID BENDIDI/Supervisory Patent Examiner, Art Unit 3664