DETAILED 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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 03/10/2026 has been entered.
Status of Application
Claims 1-20 are pending. Claims 1 and 14 are the independent claims. Claims 1 and 14 have been amended. This office action is in response to the Amendments received on 03/10/2026.
Response to Arguments
With respect to Applicant’s remarks filed on 03/10/2026 “Applicant Arguments/Remarks Made in an Amendment” have been fully considered. Applicant’s remarks will be addressed in sequential order as they were presented.
In response to the amended claims files on 03/10/2026, the objections to claim 1 has been withdrawn.
Applicant's arguments according to the Applicant’s Remarks filed on 03/10/2026, see pages 8-12 title “Rejections under 35 U.S.C § 35 U.S.C § 102 and 103”, with respect to the rejection of claims 1 and 14 under 35 U.S.C § 103 as being unpatentable over the combination of Yu, and Nakayama, have been fully considered. Applicant has amended claims 1 and 14 and argues, on page 9, first paragraph, of the Remarks, that Yu fails to teach or suggest the limitations in currently amended claims 1 and 14, particularly with regards to the limitations:
“a disturbance corrector configured to set the longitudinal acceleration input value, based on at least one of the longitudinal acceleration sensor value or an estimated inclination value estimated in a previous operation by the inclination estimator, depending on whether the vehicle stop condition is satisfied”; and,
“an estimated value initializer configured to, when a preset condition is satisfied, initialize an estimated inclination value estimated by the inclination estimator to a preset value corresponding to the preset condition, and provide the initialized estimated inclination value to the disturbance corrector as the estimated inclination value estimated in a previous operation”.
First, applicant has amended the limitation regarding the disturbance corrector feature and argues that Yu fails to disclose “a disturbance corrector configured to set the longitudinal acceleration input value, based on at least one of the longitudinal acceleration sensor value or an estimated inclination value estimated in a previous operation by the inclination estimator, depending on whether the vehicle stop condition is satisfied;”. The argument is not, respectfully, persuasive, because, according to, at least, paragraphs [0052], [0084], [0096]-[0097], [0100], [0102], Yu teaches or suggests that the longitudinal acceleration signal is biased/having noise when the vehicle is stopped and therefore the vehicle system filters the longitudinal acceleration signal to determine the static road gradient estimation (RGEST). Accordingly, filtering the longitudinal acceleration signal due to the noise before calculating the RGEST, reads on a disturbance corrector configured to set the longitudinal acceleration input value, based on at least one of the longitudinal acceleration sensor value, as recited in the claim.
Second, on page 10 of Remarks, applicant argues that Yu fails to disclose a structure in which the value that will be provided as the estimate “estimated in a previous operation” is initialized under a preset condition and then provided to the disturbance corrector, rather than a generic “input compensation” concept. The argument is not respectfully, persuasive because according to paragraph [0098] of Yu, it is disclosed that:
“[] before the start of the static RGE algorithm, information about the road gradient several seconds before the current time or several meters after the vehicle (assuming the vehicle is driving forward) shall be available from the other RGE algorithms and they are the valid reference for the static RGE algorithm to start with. After that, the static RGE algorithm takes over the main estimation task to continue monitoring the road gradient variation while the other two algorithms are paused in absence of qualified estimation conditions. More specifically, the static RGE algorithm, when estimation conditions satisfy, will take the output of either the kinematic or the dynamic estimation algorithm as its initial value depending on which one has the highest quality evaluation. []. The qualified static estimation condition is that the vehicle speed will be lower than a speed threshold and such speed threshold will be smaller than the speed thresholds that used to determine on-hold of the other two RGE algorithms.”.
According to at least this paragraph of Yu, it is disclosed that if the qualified static estimation condition is satisfied (which reads on when a preset condition is satisfied, as recited in the claim), the value of road gradient from several seconds before the current time is used as the reference to start the static RGE algorithm (which reads on initialize an estimated inclination value estimated by the inclination estimator to a preset value corresponding to the preset condition, as recited in the claim). Furthermore, in paragraph [0099] of Yu, it is disclosed that “At time t1, the vehicle starts decelerating as indicated by the decreasing slope of Vx. At time t2, the vehicle stops and the RGE becomes active. Rather than starting from 0%, and converging to the actual road gradient, the RGE starts from the last RGEkin value”. Therefore, this is the office stance that according to at least the cited parts, Yu teaches or suggests the aforementioned limitation of amended claim (See the rejection of claims 1 and 14 in the office action below).
Moreover, with respect to the limitation of “provide the initialized estimated inclination value to the disturbance corrector as the estimated inclination value estimated in a previous operation” recited in claims 1 and 14, and in light of the instant specification, it is interpreted as the estimated inclination value in a previous operation has been provided to the disturbance corrector to reduce or remove the noises and prevent amplifying the noises. Accordingly, this is the office stance that Yu teaches the aforementioned feature of the claims according to at least Fig. 10C and paragraph [0099], and also paragraphs [0052], [0100], [0126], [0102]-[0103], [0246]-[0247], and [0270]).
Office Note: Due to applicant’s amendments, further claim rejections appear on the record as stated in the below Office Action.
It is the Office’ stance that all of applicant arguments have been considered.
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 limitations are: “a vehicle information receiver”, “a vehicle stop determinator”, “a disturbance corrector”, and “an inclination estimator” in claim 1. According to the paragraphs [00155]- [00166] of the instant specification, the contents of the vehicle inclination estimation method S 100 which is fully or partially implemented by a computer device 200, may be performed and completed by a hardware processor, or may be performed and completed by a combination of hardware and software modules of the processor. Therefore, such claimed features recited in claim 1, as mentioned above, are interpreted as being software modules of the processor (or a control device), which is the structure providing the instructions and performing these functions.
Because these claim limitations are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, they 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.
Claim 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claims 1-13 and 14-20 are, respectively, directed to an apparatus and method. Therefore, claims 1-20 are within at least one of the four statutory categories. See MPEP 2106.03.
101 Analysis – Step2A, Prong I
Regarding Prong I 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 follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
In this case independent claims 1 and 14 are directed to an abstract idea without significantly more. Claim 1 recites:
“An apparatus for estimating inclination of a vehicle, the apparatus comprising: a vehicle information receiver configured to collect travel information of the vehicle including a wheel speed, a driving torque, and a longitudinal acceleration sensor value; a vehicle stop determinator configured to determine, based on the travel information received from the vehicle information receiver, whether the vehicle satisfies a vehicle stop condition; an inclination estimator configured to estimate the inclination of the vehicle using a longitudinal acceleration input value, a disturbance corrector configured to set the longitudinal acceleration input value, based on at least one of the longitudinal acceleration sensor value or an estimated inclination value estimated in a previous operation by the inclination estimator, depending on whether the vehicle stop condition is satisfied; and an estimated value initializer configured to, when a preset condition is satisfied, initialize an estimated inclination value estimated by the inclination estimator to a preset value corresponding to the preset condition, and provide the initialized estimated inclination value to the disturbance corrector as the estimated inclination value estimated in a previous operation.”
The Office submits that the foregoing bold limitation(s) constitute judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the limitations can be “performed in the human mind, or by a human using a pen and paper”. See MPEP 2106.04(a)(2)(III). For example, the limitations of determining if the vehicle stops, can be done mentally and falls under mental process that is a category of abstract idea. Also, other foregoing bold limitations, related to estimating a vehicle inclination using longitudinal acceleration value, in the context of this claim encompasses processes (i.e. mathematical process) that can be performed in human mind using pen and paper and falls under abstract idea. Accordingly, independent claim 1 recites at least one abstract idea.
101 Analysis – Step2A, Prong II
Regarding Prong II 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.”
The Office submits that the foregoing underlined limitations recite additional elements that do not integrate the recited judicial exception into a practical application.
Regarding the additional limitations of “a vehicle information receiver configured to collect travel information of the vehicle including a wheel speed, a driving torque, and a longitudinal acceleration sensor value” the examiner submits that this limitation is merely an insignificant extra-solution activity that merely use well-known techniques to collect data. Further, the additional elements of “a vehicle stop determinator”, “an inclination estimator”, “a disturbance corrector”, and “an estimated value initializer” are recited in a high level of generality and are no more than mere instructions to apply the exception using a computer.
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.
For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). 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.
101 Analysis – Step2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does 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 “a vehicle stop determinator”, “an inclination estimator”, “a disturbance corrector”, and “an estimated value initializer” amount to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the Office submits that these limitations are insignificant extra-solution activities.
Claim 14 is also not patent eligible for the same reasons as stated in the above claim 1 rejection.
Dependent claims 2-13, and 15-20 have been given the full two-part analysis, including analyzing the additional limitations, both individually and in combination. The dependent claims, when analyzed both individually and in combination, are also patent ineligible under 35 U.S.C. § 101 based on the same analysis as above. The aforementioned dependent claims, further recite additional steps of mathematical process and can be done in human mind with pen and paper which falls under abstract idea. Further, the additional limitations recited in the dependent claims fail to establish that the dependent claims are not directed to an abstract idea. The additional limitations of the dependent claims, when considered individually and as an ordered combination, do not amount to significantly more than the abstract idea. Accordingly claims 2-13 and 15-20 are also patent ineligible.
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.
Claims 1-4, 10-11, 14-16 and 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Yu at al., US 20140067154 A1, hereinafter “Yu”, in view of Nakayama US 20070173984 A1, hereinafter “Nakayama”.
Regarding claims 1 and 14, Yu discloses an apparatus and method for estimating inclination of a vehicle (e.g., Abstract, Fig.2, [0037], “a vehicle system for estimating road gradient”, [0052],[0053],[0079], [0162] __road gradient reads on inclination of a vehicle, Examiner Note: Under the broadest reasonable interpretation of the examiner according to the specification of the instant application, for example, paragraphs [0003]-[0006], Fig.2 and paragraph [0064], “The inclination of the vehicle may have a value substantially the same as or similar to that of inclination of the road.”, the inclination of a vehicle is considered as inclination of the road__) the apparatus comprising: a vehicle information receiver configured to collect travel information of the vehicle including a wheel speed, a driving torque, and a longitudinal acceleration sensor value ([0037], “The VSC (Vehicle System Controller) receives input that corresponds to vehicle speed (Vx), acceleration (a), yaw rate (r) and torque (T.sub.pwt, T.sub.brk),”, [0045], “sensor 52 provide output corresponding to longitudinal acceleration”) and an inclination estimator configured to estimate the inclination of the vehicle using a longitudinal acceleration input value (set in the disturbance correction operation _ as recited in claim 14- ) (e.g., [0052] “estimates road gradient based on the longitudinal acceleration input”, claim 13, “estimate the vehicle pitch angle using a dynamic pitch compensation based on a vehicle speed and the longitudinal acceleration”, __vehicle pitch angle reads on the inclination of the vehicle and pitch compensation reads on disturbance corrector that is performed by compensating for the biased in the value of the longitudinal acceleration according to, for example, paragraphs [0052], [0162], and [0163], “compensation strategy for estimating the vehicle pitch angle”, “estimates the pitch angle (.theta.) based on … the vehicle longitudinal acceleration (a.sub.x.sup.s).”, [0173], Eq. (49), __Note: also further see paragraphs [0084], [0096], [0097], [0100], [0102], teaching filtering the longitudinal acceleration signal due to noise before estimating the RGE which reads on longitudinal acceleration value set in the disturbance correction operation, as recited in claim 14 __), a disturbance corrector configured to set the longitudinal acceleration input value, based on at least one of the longitudinal acceleration sensor value or an estimated inclination value estimated in a previous operation by the inclination estimator, depending on whether the vehicle stop condition is satisfied ([0052], [0084], [0096]-[0097], [0100], [0102], Note: filtering the longitudinal acceleration signal due to the noise before calculating the RGEST, reads on a disturbance corrector configured to set the longitudinal acceleration input value, based on at least one of the longitudinal acceleration sensor value, as recited in the claim); an estimated value initializer configured to when a preset condition is satisfied, initialize an estimated inclination value estimated by the inclination estimator to a preset value corresponding to the preset condition ( [0098]-[0099], See section Response to Arguments, Pages 4 and 5, paragraphs 8 and 9 of the present office action) and provide the initialized estimated inclination value to the disturbance corrector as the estimated inclination value estimated in a previous operation (Note: this limitation has been interpreted in light of the instant application specification as the estimated inclination value in a previous operation is provided to the disturbance corrector to reduce/remove the noises and prevent amplifying the noises. Accordingly, See at least Yu, Fig. 10C and paragraph [0099], and also paragraphs [0052], [0100], [0126], [0102]- [0103], [0246]-[0247], and [0270]).
Yu doesn’t explicitly disclose a vehicle stop determinator configured to determine, based on the travel information received from the vehicle information receiver, whether the vehicle satisfies a vehicle stop condition;
However, Nakayama teaches a vehicle stop determinator configured to determine, based on the travel information received from the vehicle information receiver, whether the vehicle satisfies a vehicle stop condition ([0002], [0012], “a stop determination apparatus which is capable of making a proper determination of a stop of a vehicle,”, [0014]);
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the vehicle system for estimating road gradient as taught by Yu, with a vehicle stop determinator as taught by Nakayama and a disturbance corrector as taught by Yu, with a reasonable expectation of success, with the motivation of improving the accuracy of the estimated of the vehicle inclination because according to motion state/dynamic of the vehicle (particularly stopping state), there would be different level of disturbance/error in estimations which would affect the accuracy of the inclination estimation. Therefore, detecting the state of the vehicle dynamics and the corresponding created errors in the estimation of the vehicle inclination and correcting them, would improve the accuracy of the results.
Regarding claim 2, Yu in view of Nakayama teaches the apparatus of claim 1, and Nakayama teaches wherein the vehicle stop condition is set based on the wheel speed received from the vehicle information receiver, or based on the wheel speed and the driving torque received from the vehicle information receiver ([0007], “a vehicle speed sensor for detecting the rotational speed of the drive wheels and which utilize its output for determination of a stop of the vehicle”, [0070]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the vehicle system for estimating road gradient as taught by Yu, with a vehicle stop determinator based on the received wheel speed information as taught by Nakayama, with a reasonable expectation of success, with the motivation of improving the accuracy of the estimated values of the vehicle inclination considering the motion state/dynamic of the vehicle (particularly stopping state).
Regarding claims 3 and 15, Yu in view of Nakayama teaches the apparatus and method of claims 1 and 14, and Yu teaches wherein the disturbance corrector (See the rejection for claim 1 regarding the teaching of disturbance corrector) is configured to set a value obtained by removing the longitudinal acceleration sensor value ([0008], “using input compensated acceleration offset”, [0081], “Since the vehicle is static, or at standstill, […] the longitudinal acceleration ({dot over (V)}.sub.x), […] set to zero” __under the broadest reasonable interpretation of the examiner, setting the longitudinal acceleration to zero in standstill state reads on removing the longitudinal acceleration value if the vehicle is in the stop condition as recited in the claim__) or lowering a proportion of the longitudinal acceleration sensor value as the longitudinal acceleration input value input to the inclination estimator, in response that the vehicle stop condition is satisfied ([0052], [0084], [0100], “After the vehicle stops, there is noise present on the longitudinal acceleration signal […] The vehicle system filters the longitudinal acceleration signal (a.sub.x.sup.s) using a low pass filter, __filtering the longitudinal acceleration signal due to the present noise after the vehicle stops, reads on lowering a proportion of the longitudinal acceleration in order to correct the disturbance__, [0103]).
Regarding claim 4 and 16, Yu teaches wherein the travel information collected by the vehicle information receiver further includes a lateral speed and a yaw rate of the vehicle, and wherein the inclination estimator is configured to estimate the inclination of the vehicle through a Kalman filter using the lateral speed, the yaw rate, and the longitudinal acceleration sensor value as input thereof (e.g., [0048], [0053]).
Regarding claims 10 and 18, Yu teaches the apparatus of claim 4 and method of claim16, wherein the estimated value initializer is configured to initialize the estimated inclination value to inclination corresponding to the longitudinal acceleration sensor value or inclination corresponding to a value obtained by processing the longitudinal acceleration sensor value with a low-pass filter (LPF), in response that the vehicle stop condition is satisfied ([0096], “ the vehicle system estimates an initial value for RGE.sub.st based on either the kinematic or dynamic road gradient estimates, and then filters the longitudinal acceleration signal (a.sub.x.sup.s) using a low pass filter having a variable bandwidth to determine RGE.sub.st”, __table on page 4 shows different scenario including standstill condition of the vehicle__).
Regarding claim 11, Yu teaches wherein the estimated value initializer is configured to process the longitudinal acceleration sensor value with the LPF, in response that a low-speed condition in which a vehicle speed has a preset value or is less than the preset value is satisfied (2014, Fig 8, element 812 and 818).
Regarding claim 20, Yu discloses a computer-readable storage medium recording a program for executing the method described in claim 14 on a computer ([0047], “memory”, “code”, [0049]).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Yu, in view of Nakayama or as an alternative rejection for one the recited limitation in view of Shatters et al., US 20230359209 A1, hereinafter “Shatters” , and further in view of Hiroo, WO 2022054170 A1, hereinafter “Hiroo”.
Regarding claim 5, although Yu teaches a weight setting unit configured to schedule, based on vehicle information received from the vehicle information receiver, a Q gain, a system error of the Kalman filter, depending on a travel situation ([0118]-[0119], [0165], “phase plane gain scheduling rule”, __gain scheduling rule reads on weight setting unit recited in the claim__), however, for the purpose of compact prosecution and in alternative rejection, Shatters also teaches a weight setting unit configured to schedule, based on vehicle information received from the vehicle information receiver, a Q gain, a system error of the Kalman filter, depending on a travel situation. ([0028], “to optimize the weight assigned to estimated or predicted values”, “During each iteration performed by the Kalman filter, a “gain” or weighting is determined by comparing an error in the estimate for a measured value and an error in the actual measurement of the value.”, [0038], “A gain schedule module may be configured to calculate weights (or gains)”, __optimizing/determining the weight assigned to the estimated values and also a gain schedule module meet the claim limitation. Gain schedule module reads on a weight setting unit__, [0047]- [0048]),
Yu doesn’t explicitly teach wherein the weight setting unit is configured to set a first Q gain in response that the vehicle stop condition is satisfied, and to set a second Q gain in response that a condition before stopping, corresponding to a situation before the vehicle is stopped, is satisfied.
However, Hiroo teaches wherein the weight setting unit is configured to set a first Q gain in response that the vehicle stop condition is satisfied, and to set a second Q gain in response that a condition before stopping, corresponding to a situation before the vehicle is stopped, is satisfied (Under the broadest reasonable interpretation of the examiner, a situation before the vehicle is stopped can be interpreted as on when the vehicle is not in stop condition or it is in motion state. Hiroo teaches using different Q gains according to the different speed ranges which reads on the limitation, Hiroo, Fig. 6 (table TBL) and Fig 7, [0010]/[fig.6], “a Kalman filter gain and a system matrix depending on a vehicle speed”, __Paragraph [0031] discloses using different gain for different speed ranges which is not limited to the ranges recited in the paragraph. Speed 0 (in the speed rang of 0-30 km/h reads on vehicle is stopped and the other values can read on when the vehicle is moving __, and paragraph [0036]).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the vehicle system for estimating road gradient as taught by Yu, with a weight setting unit as taught by Yu (or Shatters, in alternative) and adjusting Q gains by setting different Q gains when the vehicle is stopped and when it is in the pre-stopping condition as taught by Hiroo, with a reasonable expectation of success, because using different Q gains for vehicle stopping and pre-stopping conditions, optimize the Kalman’s filter’s performance for inclination estimation by balancing the response to noise, leading to more accurate, and reliable information.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Yu, in view of Nakayama and as an alternative rejection for one the recited limitation in view of Shatters further in view of Hiroo.
Regarding claim 6, Yu in view of aforementioned prior arts the apparatus of claim 5 and Yu teaches wherein the disturbance corrector (See the rejection for claim 1 regarding the teaching of disturbance corrector) is configured to: set a value obtained by removing the longitudinal acceleration sensor value ([0008], “using input compensated acceleration”, [0081], “Since the vehicle is static, or at standstill, […] the longitudinal acceleration ({dot over (V)}.sub.x), […] set to zero”, __under the broadest reasonable interpretation of the examiner, setting the longitudinal acceleration to zero in standstill state reads on removing the longitudinal acceleration value if the vehicle is in the stop condition as recited in the claim__) or lowering a proportion of the longitudinal acceleration sensor value as the longitudinal acceleration input value input to the inclination estimator, in response that the vehicle stop condition is satisfied ([0052], [0084], [0100], “After the vehicle stops, there is noise present on the longitudinal acceleration signal […] The vehicle system filters the longitudinal acceleration signal (a.sub.x.sup.s) using a low pass filter, __filtering the longitudinal acceleration signal due to the present noise after the vehicle stops, reads on lowering a proportion of the longitudinal acceleration in order to correct the disturbance__, [0103]) and set the longitudinal acceleration sensor value as the longitudinal acceleration input value input to the inclination estimator, in response that the vehicle stop condition is not satisfied (at least, [0053], “The kinematic RGE algorithm 424 is suited for normal vehicle motion conditions (e.g., Vx>5 kph)”, __the kinematic RGE algorithm which uses longitudinal acceleration value as an input, according to at least the cited paragraphs, is used for normal vehicle motion, for example, with velocity greater that 5 kph which reads on the claim limitation of not satisfying the vehicle stop condition__, [0104]-[0105], [0129]. Fig. 13D, [0245], “The vehicle system evaluates the RGE (Road Gradient Slope) input signal quality and processing […] The vehicle longitudinal acceleration is an input signal 414 and is measured from an inertia sensor 52 (shown in FIG. 1).”).
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Yu, in view of Nakayama and as an alternative rejection for one the recited limitation in view of Shatters further in view of Hiroo, further in view of Chen et. al, CN 113771857 B, hereinafter “Chen”.
Regarding claim 7, the aforementioned prior arts teach the apparatus of claim 6, However, the aforementioned prior arts don’t explicitly teach wherein the first Q gain is set to have a value less than a value of the second Q gain,
However, Chen teaches wherein the first Q gain is set to have a value less than a value of the second Q gain (__[n0119] teaches the limitation of the claim which is setting higher Q for the vehicle is moving (not stepped) than a condition that the vehicle is stopped__, [n0120] “adjustment of the process noise Q covariance matrix According to the system state equation can be seen, process noise depends on the vehicle longitudinal acceleration (or wheel acceleration) absolute value of the size of the longitudinal acceleration absolute value is larger, indicating the process noise is larger, Q should be properly increased; otherwise, longitudinal acceleration absolute value is smaller, indicating that the process noise is smaller, Q should be properly reduced.”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the vehicle system for estimating road gradient as taught by Yu in view of Nakayama, with a weight setting unit as taught by Yu (or Shatters, in alternative) and adjusting Q gains by setting different Q gains when the vehicle is stopped and when it is in the pre-stopping condition as taught by Hiroo and further using a lower Q gain value when the vehicle in in stopped condition than when the vehicle is in the pre-stopping condition, with a reasonable expectation of success, with the motivation of improving the accuracy and stability of the estimation. When the vehicle is stopped a lower Q gain reduces the filter’s sensitivity to noise, keeping the inclination estimation steady. In contrast, when the vehicle is still moving or slowing down (pre-stopping condition), a higher Q gain allows the filter to respond more quickly to real changes and disturbances. This helps the Kalman filter produce more reliable inclination estimates across different vehicle motion states.
Regarding claim 17, claim recites similar limitations as in claims 5 and 7 (See the rejections for claim 5 and 7)
Claims 8 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Yu, in view of Nakayama and as an alternative rejection for one the recited limitation in view of Shatters further in view of Hiroo, further in view of Chen and further in view of Ono et al., US 8706376 B2, hereinafter “Ono”.
Regarding claim 8, Yu in view of aforementioned arts relied upon teaches the apparatus of claim 6, however Yu doesn’t explicitly disclose the weight setting unit is configured to set a third Q gain, in response that a vehicle speed is in a setting range in an anti-lock braking system (ABS) operation state, and wherein the second Q gain is set to have a value greater than a value of the first Q gain and less than a value of the third Q gain.
Nevertheless, Hiroo teaches wherein the weight setting unit is configured to set a third Q gain, in response that a vehicle speed is in a setting range (Fig. 6 (table TBL) and Fig 7, [0010]/[fig.6], “a Kalman filter gain and a system matrix depending on a vehicle speed”, __Paragraph [0031] discloses using different gain for different speed ranges which is not limited to the ranges recited in the paragraph. Speed 0 (in the speed rang of 0-30 km/h reads on vehicle is stopped and the other values can read on when the vehicle is moving __ Page 5, paragraph [0036])).
Nevertheless, Chen teaches wherein the second Q gain is set to have a value greater than a value of the first Q gain and less than a value of the third Q gain ( [n0119]-[n0120] “adjustment of the process noise Q covariance matrix According to the system state equation can be seen, process noise depends on the vehicle longitudinal acceleration (or wheel acceleration) absolute value of the size of the longitudinal acceleration absolute value is larger, indicating the process noise is larger, Q should be properly increased; otherwise, longitudinal acceleration absolute value is smaller, indicating that the process noise is smaller, Q should be properly reduced.”, __ the claim is interpreted as setting higher Q gain for the higher vehicle speed (third gain corresponding to a speed is higher that a second gain corresponding to the condition before stopping (reducing speed) and it is also higher than the first Q gain according to the stopped condition (zero speed). According to the cited reference, Q gain should be higher for the higher speed level of the vehicle which meets the claim’s limitation__)
Nevertheless, Ono teaches a vehicle speed is in a setting range in an anti-lock braking system (ABS) operation state (at least, Col 2, Lines 43-46 “ABS control system automatically calibrates an internal parameter used in ABS control in response to the wheel speed”, __this reads on ABS having different conditions based on the speed__)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the vehicle system for estimating road gradient as taught by Yu in view of Nakayama, with a weight setting unit as taught by Yu (or Shatters, in alternative) and adjusting Q gains based on different speed ranges as taught by Hiroo and using higher Q value when vehicle is in higher speed as taught by chen, in a vehicle system equipped with ABS states settings based on vehicle speed ranges as taught by Ono, with the motivation of allowing the estimator to adapt rapidly to real-world changes and improving the accuracy of the estimated inclination value in different dynamic driving scenario. Using higher Q gain in Kalman filter for estimating the inclination at higher vehicle speed allows the filter to respond more quickly to dynamic changes and disturbance in the system.
Regarding claim 9, Yu in view of aforementioned arts relied upon teaches the apparatus of claim 6, however, Yu doesn’t explicitly disclose wherein a condition of an anti-lock braking system (ABS) operation state includes a first ABS condition and a second ABS condition having a vehicle speed higher than a vehicle speed of the first ABS condition, wherein the weight setting unit is configured to set a third Q gain, in response that the first ABS condition is satisfied, and to set a fourth Q gain, in response that the second ABS condition is satisfied, and wherein the fourth Q gain is set to have a value greater than a value of the third Q gain.
However, Ono teaches wherein a condition of the ABS operation state includes a first ABS condition and a second ABS condition having a vehicle speed higher than a vehicle speed of the first ABS condition (at least, Col 2, Lines 43-46 “ABS control system automatically calibrates an internal parameter used in ABS control in response to the wheel speed”, __this reads on ABS having different conditions based on the speed__)
However, Hirro teaches wherein a condition having a vehicle speed higher than a vehicle speed, wherein the weight setting unit is configured to set a third Q gain, in response that the first ABS condition is satisfied, and to set a fourth Q gain, in response that the second ABS condition is satisfied (Under the broadest reasonable interpretation of the examiner, first ABS condition refers to the first speed range and second ABS condition refers to the second speed range of the vehicle which is higher than the first range. Therefore, based on the same teaching as recited in the rejections of claim 7, Hiroo teaches using different Q gain for different speed range (See the cited paragraph in the mapping of claim 8).
Further, Chen teaches wherein the fourth Q gain is set to have a value greater than a value of the third Q gain (Chen explicitly discloses that the value of Q gain should be set as greater in higher vehicle speed (See the cited paragraphs in the mapping of claim 7 or 8))
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the vehicle system for estimating road gradient as taught by Yu in view of Nakayama, with a weight setting unit as taught by Yu (or Shatters, in alternative) and adjusting Q gains based on different speed ranges as taught by Hiroo and using higher Q value when vehicle is in higher speed as taught by chen, in a vehicle system equipped with ABS states settings based on vehicle speed ranges as taught by Ono, with the motivation of allowing the estimator to adapt rapidly to real-world changes and improving the accuracy of the estimated inclination value in different dynamic driving scenario. Using higher Q gain in Kalman filter for estimating the inclination at higher vehicle speed allows the filter to respond more quickly to dynamic changes and disturbance in the system.
Claims 12, 13 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Yu, in view of Nakayama, and further in view of Sawada et al. US 20180015840 A1, hereinafter “Sawada”.
Regarding claims 12 and 19, Yu in view of aforementioned prior arts relied upon teaches the apparatus of claim 10 and claim of claim 18 and although Yu teaches”, and wherein the initialized estimated inclination value is input to the inclination estimator (e.g., [0096], [0098], “estimates an initial value for RGEst (static road gradient estimation) based on either the kinematic or dynamic road gradient estimates.” “Since the static RGE (Road Gradient Estimation) function only starts after the vehicle speed is lower than a predefined speed threshold, (e.g., lkph), the initial value of the estimation algorithm is a factor in the convergence time, or the time delay until RGE.sub.st converges to the actual road gradient.”, [0102], “using an initial value for RGEst” ,[0123]), however, Yu doesn’t explicitly teaches wherein the estimated value initializer is configured to initialize the estimated inclination value to the inclination corresponding to the longitudinal acceleration sensor value, in response that a condition before stopping is satisfied.
However, Sawada et al. US 20180015840 A1, teaches wherein the estimated value initializer is configured to initialize the estimated inclination value to inclination corresponding to the longitudinal acceleration sensor value, in response that a condition before stopping is satisfied ([0080], “In case…determines that the electric motor vehicle is just before the stop of the vehicle … the motor rotation speed estimator 604 initializes the vehicle simple model Gp″(s) based on the current motor rotation speed ωm.”, “setting the initial value of the above-described integrator to the motor rotation speed”, __ The cited reference uses the same strategy as recited in the claim but for estimating motor rotation speed instead of vehicle inclination. Therefore, the reference teaches the method which can be used in calculating any relevant parameters like inclination value (using an estimated value as an initial value) and it is obvious to substitute motor rotation speed estimator in the disclosed method with the inclination estimator and also substitute initializing the value with the corresponding value__)
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to include the vehicle system for estimating road gradient as taught by Yu, with the step of using estimated inclination value based on the longitudinal acceleration as an initial value in the inclination estimator when the vehicle is in before stopping condition, with the reasonable expectation of success, with the motivation of providing a stable and reasonable starting point for the inclination estimation process when the vehicle is before stopping (less dynamic disturbance due to high speed) by using the data from sensors (like acceleration sensor) before being less informative or biased due to lack of movement (full stop). This improves overall estimation accuracy.
Regarding claim 13, Yu teaches the apparatus of claim 12, wherein the estimated inclination value initialized by the estimated value initializer is input to the disturbance corrector and used for disturbance correction (0052], “algorithm compensates for the vehicle pitch angle,”, [0123], [0126], “the vehicle system initializes estimator parameter values”, [0133], “the vehicle system estimates …the vehicle pitch angle (.theta.) using a vehicle body relative pitch effect compensation strategy.”, __compensation strategy reads on disturbance corrector__, [0171], “The vehicle system uses the third compensation strategy to estimate the pitch angle”).
Conclusion
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/H.H./Examiner, Art Unit 3669
/NAVID Z. MEHDIZADEH/Supervisory Patent Examiner, Art Unit 3669
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