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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 April 27, 2026 has been entered.
Status of the Claims
This action is in response to the applicant’s amendment/response and RCE of April 27, 2026.
Claim 31 has been canceled.
Claim 32 has been newly added.
Claims 1-4, 6-11, 13-18, 20, 29, 30, and 32 are pending and have been considered as follows.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on February 11, 2026 and April 27, 2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant’s arguments/amendments with respect to the objection to the claims have been fully considered and are persuasive. Therefore, the objection to the claims as presented in the Office Action of January 27, 2026 has been withdrawn. However, new objection to the claims is presented below based on the amendments to the claims presented in the Amendment of 27 April 2026.
Applicant’s arguments/amendments with respect to the rejection of claims under 35 USC § 101 have been fully considered and are not persuasive.
Specifically, applicant argues:
1. The claims are patent eligible because the claims do not recite any judicial exceptions under Prong 1
As stated in the 2019 Guidance, if the claim does not recite a judicial exception, it is not directed to a judicial exception (Step 2A: NO) and is eligible. As discussed below, Applicant submits that the claim does not recite a judicial exception under Prong 1, and therefore is eligible.
Here, the Examiner asserts that the claims recite features that amount to "can reasonably be performed in the human mind or by a human using a pen and paper, otherwise considered a mental process, which is an abstract idea." Office Action, p. 11. In particular, the examiner alleges that "the claim encompasses a user (person) simply generating, using the sparse location data and the motion data, a dense data set to reconstruct a route, an alignment of the dense data set between the starting data point and the ending data point based at least in part on the sparse location data, the motion data, and the road segment information in his/her mind or by a human using a pen and paper.
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Applicant respectfully submits that the claims cannot "reasonably be performed in the human mind or by a human using a pen and paper, otherwise considered a mental process, which is an abstract idea" as the Examiner has asserted at page 11 of the Office Action, but rather, the claims are directed to reconstructing a route, and determining to generate a recommendation for improving driving deficiency based on a first energy usage for a first trip along the route and second energy usage for a simulated trip with adjusted driving parameters along the route. Applicant respectfully submits that the claims do not recite any of the judicial exceptions enumerated in the 2019 Guidelines. For instance, the claims do not recite any mathematical relationships, formulas, or calculations. Further, the claims do not recite any method of organizing human activity such as a fundamental economic concept or managing interactions between people. Finally, the claims do not recite a mental process because the steps are not practically performed in the human mind.
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2. Even if, arguendo, the claims are directed to an abstract idea, the claims integrate the abstract idea into a practical application such that the claims are patent eligible.
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Applicant respectfully submits that, even if, arguendo, the claims are directed to a judicial exception, the claims integrate that judicial exception into a practical application. For example, Applicant respectfully submits that the features of claim 1 impose meaningful limits on any alleged judicial exception.
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Applicant respectfully submits that the claims, at least as amended, are directed to a technical improvement. One reason is that the claims are directed to a technical improvement of utilizing first energy usage for a first trip along a route and second energy usage, based at least in part on one or more adjusted driving parameters, for a simulated trip along the route to determine whether to generate a recommendation for improving driving efficiency.
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3. Even if, arguendo, the claims are abstract, the claims amount to significantly more than the abstract idea and thus qualify as eligible subject matter under 35 U.S.C. §101.
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Applicant submits that the features of claim 1 are combined in a way that is a non-conventional and non-generic, and that includes an inventive concept. This is evidenced by the fact that the limitations relate to an improvement of energy usage (e.g., reducing the energy usage through recommendation based on first energy usage for the first trip and second energy usage for the simulated trip), and do not preempt other implementations of energy usage management and recommendations. Thus, just like the claims in Bascom, the claims in this application include an inventive concept. Therefore, even if the claims are directed to an abstract idea, which Appellant expressly denies, the claims are nevertheless directed to a patentable idea that is significantly more than the alleged abstract idea.
The Examiner’s Response
The Examiner has carefully considered applicant’s arguments and respectfully disagrees. Applicant asserts that “1. The claims are patent eligible because the claims do not recite any judicial exceptions under Prong 1. … Applicant respectfully submits that the claims do not recite any of the judicial exceptions enumerated in the 2019 Guidelines. For instance, the claims do not recite any mathematical relationships, formulas, or calculations. Further, the claims do not recite any method of organizing human activity such as a fundamental economic concept or managing interactions between people. Finally, the claims do not recite a mental process because the steps are not practically performed in the human mind.” However, the Examiner respectfully disagrees. While Applicant asserts the steps in claim 1, such as “after a conclusion of the first time period, generating, using the sparse location data and the motion data, a dense data set to reconstruct a route, an alignment of the dense data set between the starting location data point and the ending location data point based at least in part on the sparse location data, the motion data, and the road segment information”, “determining first energy usage for the first trip along the route, the first energy usage based at least in part on one or more driving parameters for the first trip along the route”, “determining second energy usage for a simulated trip along the route, the second energy usage based at least in part on one or more adjusted driving parameters, the one or more adjusted driving parameters being adjusted from the one or more driving parameters”, and “determining to generate a recommendation for improving driving efficiency based at least in part on the first energy usage and the second energy usage” could not be performed in the human mind, under its broadest reasonable interpretation, these limitations can reasonably be performed by a human mentally or with aid of pen and paper, otherwise considered a mental process, which is an abstract idea.
Further, Applicant asserts that “2. Even if, arguendo, the claims are directed to an abstract idea, the claims integrate the abstract idea into a practical application such that the claims are patent eligible. … Applicant respectfully submits that, even if, arguendo, the claims are directed to a judicial exception, the claims integrate that judicial exception into a practical application. For example, Applicant respectfully submits that the features of claim 1 impose meaningful limits on any alleged judicial exception. … Applicant respectfully submits that the claims, at least as amended, are directed to a technical improvement. One reason is that the claims are directed to a technical improvement of utilizing first energy usage for a first trip along a route and second energy usage, based at least in part on one or more adjusted driving parameters, for a simulated trip along the route to determine whether to generate a recommendation for improving driving efficiency.” However, the Examiner respectfully disagrees. The Examiner submits that the claim recites the additional elements of “accessing sparse location data indicative of one or more geographic locations along a route of the user device during a first time period, the route including a starting location data point and an ending location data point, the first sparse location data corresponding to a first trip along the route”, “accessing motion data collected by one or more sensors of the user device, the motion data collected by the one or more sensors during the first time period”, “accessing road segment information from a map application based at least in part on accessing the sparse location data and accessing the motion data”, and “storing the reconstructed route in a local memory of the user device”, and these additional details do not integrate the judicial exception into a practical application. The accessing steps do not elevate this limitation from insignificant extra-solution data gathering. The storing step does not elevate this limitation from insignificant extra-solution activity. The claims as a whole merely describe how to generally “apply” the otherwise mental judgments in a generic or general purpose computing environment.
Moreover, the Examiner respectfully disagrees with the argument because the Applicant is not making a claim to improving the technology and there is no improvement in the function of the technology itself, and therefore these cited improvements do not meet the threshold to integrate the judicial exception into a practical application. The Examiner submits that the improvement recited in the claims is merely to the processing of information, not to a computer itself, which is thus an improved mental process, not an improvement to the computer or technology. An improved abstract idea is still an abstract idea (see Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016) ("a *new* abstract idea is still an abstract idea"). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to the abstract idea.
Furthermore, Applicant asserts that “3. Even if, arguendo, the claims are abstract, the claims amount to significantly more than the abstract idea and thus qualify as eligible subject matter under 35 U.S.C. §101. … Applicant submits that the features of claim 1 are combined in a way that is a non-conventional and non-generic, and that includes an inventive concept. This is evidenced by the fact that the limitations relate to an improvement of energy usage (e.g., reducing the energy usage through recommendation based on first energy usage for the first trip and second energy usage for the simulated trip), and do not preempt other implementations of energy usage management and recommendations. Thus, just like the claims in Bascom, the claims in this application include an inventive concept. Therefore, even if the claims are directed to an abstract idea, which Appellant expressly denies, the claims are nevertheless directed to a patentable idea that is significantly more than the alleged abstract idea.” However, the Examiner respectfully disagrees. The Examiner submits that the claim does not recite any specific limitation or combination of limitations that are not well-understood, routine, conventional (WURC) activity in the field. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Moreover, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the additional elements in the claims amount to no more than insignificant extra-solution activity. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere performance of an action is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). As set forth in MPEP 2106.05(a)(II), “it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. For example, in Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology”. Therefore, the rejection of such claims under 35 USC § 101 rejection is maintained herein.
Examiner notes that the rejection has been modified reflecting the amendments most recently submitted by applicant.
Applicant’s arguments/amendments with respect to the rejection of claims under 35 USC § 103 have been fully considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Objections
Claims 1, 8, and 15 are objected to because of the following informalities:
Claim 1, line 12, “a route” should read “the route”.
Claim 8, line 14, “a route” should read “the route”.
Claim 15, line 13, “a route” should read “the route”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-4, 6-11, 13-18, 20, 29, 30, and 32 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
As to claim 1, the limitation “the first sparse location data” at line 5 is unclear. There is insufficient antecedent basis for this limitation in the claim. For purposes of examination, the Examiner is interpreting the limitation to be “a first sparse location data”.
As to claim 8, the limitation “the first sparse location data” at line 7 is unclear. There is insufficient antecedent basis for this limitation in the claim. For purposes of examination, the Examiner is interpreting the limitation to be “a first sparse location data”.
As to claim 15, the limitation “the first sparse location data” at line 6 is unclear. There is insufficient antecedent basis for this limitation in the claim. For purposes of examination, the Examiner is interpreting the limitation to be “a first sparse location data”.
Claims 2-4, 6, 7, 9-11, 13, 14, 16-18, 20, 29, 30, and 32 are rejected as being dependent upon a rejected claim.
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 1-4, 6-11, 13-18, 20, 29, 30, and 32 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In January, 2019 (updated October 2019), the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1, 8, and 15 are directed toward non-statutory subject matter, as shown below:
STEP 1: Do claims 1, 8, and 15 fall within one of the statutory categories? Yes. The claims are directed toward a machine and a process which falls within one of the statutory categories.
STEP 2A (PRONG 1): Are the claims directed to a law of nature, a natural phenomenon or an abstract idea? Yes, the claims are directed to an abstract idea.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The independent claims (claims 1, 8, and 15) recite the limitation of “after a conclusion of the first time period, generate/generating, using the sparse location data and the motion data, a dense data set to reconstruct a route, an alignment of the dense data set between the starting location data point and the ending location data point based at least in part on the sparse location data, the motion data, and the road segment information”, “determine/determining first energy usage for the first trip along the route, the first energy usage based at least in part on one or more driving parameters for the first trip along the route”, “determine/determining second energy usage for a simulated trip along the route, the second energy usage based at least in part on one or more adjusted driving parameters, the one or more adjusted driving parameters being adjusted from the one or more driving parameters”, and “determine/determining to generate a recommendation for improving driving efficiency based at least in part on the first energy usage and the second energy usage”. Under its broadest reasonable interpretation, this limitation, as drafted, can reasonably be performed in the human mind or by a human using a pen and paper, otherwise considered a mental process, which is an abstract idea. For example, the claim limitations encompass a person looking at (observing) the data and determines a dense data set; and reconstructs a route; calculates first energy usage for the first trip along the route; calculates second energy usage for a simulated trip along the route; and determines a recommendation for improving driving efficiency based at least in part on the first energy usage and the second energy usage. 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 such, the claim encompasses a user (person) simply generating, using the sparse location data and the motion data, a dense data set to reconstruct a route, an alignment of the dense data set between the starting location data point and the ending location data point based at least in part on the sparse location data, the motion data, and the road segment information; determining first energy usage for the first trip along the route, the first energy usage based at least in part on one or more driving parameters for the first trip along the route; determining second energy usage for a simulated trip along the route, the second energy usage based at least in part on one or more adjusted driving parameters, the one or more adjusted driving parameters being adjusted from the one or more driving parameters; and determining to generate a recommendation for improving driving efficiency based at least in part on the first energy usage and the second energy usage in his/her mind or by a human using a pen and paper. The mere nominal recitation of a user device (claims 1, 5, and 15), one or more sensors (claims 1, 5, and 15), one or more processors (claims 8 and 15), one or more memories (claim 8), or one or more non-transitory computer-readable media (claim 15) does not take the claim limitation out of the mental processes grouping. Thus, the claim recites a mental process.
STEP 2A (PRONG 2): Do the claims recite additional elements that integrate the judicial exception into a practical application? No, the claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses 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 more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claims 1, 8, and 15 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. This judicial exception is not integrated into a practical application because the claim(s) recites additional elements of “access/accessing sparse location data indicative of one or more geographic locations along a route of the user device during a first time period, the route including a starting location data point and an ending location data point, the first sparse location data corresponding to a first trip along the route”, “access/accessing motion data collected by one or more sensors of the user device, the motion data collected by the one or more sensors during the first time period”, “access/accessing road segment information from a map application based at least in part on accessing the sparse location data and accessing the motion data”, “store/storing the reconstructed route in a local memory of the user device”, a user device (claims 1, 5, and 15), one or more sensors (claims 1, 5, and 15), one or more processors (claims 8 and 15), one or more memories (claim 8), and one or more non-transitory computer-readable media (claim 15). The accessing steps are recited at a high level of generality (i.e. as a general means of receiving/gathering data) and amount to no more than data gathering, which is a form of extra solution activity. The storing step is recited at a high level of generality and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. The one or more sensors in claims 1, 5, and 15 are claimed generically and operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Regarding the additional limitation(s) of “a user device” in claims 1, 5, and 15, “one or more processors” in claims 8 and 15, “one or more memories” in claim 8, and “one or more non-transitory computer-readable media” in claim 15, the Examiner submits the limitations are merely tool(s) being used to perform the abstract idea (or instructions to implement the abstract idea on a computer). Further, the “a user device”, “one or more processors”, “one or more memories”, and “one or more non-transitory computer-readable media” are recited at a high level of generality and amounts to no more than mere instructions to apply the exception using a generic computer. The component(s) merely automate(s) the aforementioned step(s) and thus do/does not integrate a judicial exception into a “practical application”. See MPEP 2106.05(f). These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of computers. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to the abstract idea.
STEP 2B: Do the claims recite additional elements that amount to significantly more than the judicial exception? No, the claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
The claim(s) does/do not recite any specific limitation or combination of limitations that are not well-understood, routine, conventional (WURC) activity in the field. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “the user device”, the one or more sensors”, “the one or more processors”, “the one or more memories”, and “the one or more non-transitory computer-readable media” amount to nothing 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 claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the additional elements in the claims amount to no more than insignificant extra-solution activity. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere performance of an action is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
CONCLUSION
Thus, since claims 1, 8, and 15 are: (a) directed toward an abstract idea, (b) does not recite additional elements that integrate the judicial exception into a practical application, and (c) does not recite additional elements that amount to significantly more than the judicial exception, it is clear that claims 1, 8, and 15 are directed towards non-statutory subject matter.
Examiner additionally notes claims 2-4, 6, 7, 29, and 32 depend from claim 1, claims 9-11, 13, 14, and 30 depend from claim 8, and claims 16-18, and 20 depend from claim 15.
Dependent claims 2-4, 6, 7, 9-11, 13, 14, 16-18, 20, 29, 30, and 32 further limit the abstract idea without integrating the abstract idea into practical application or adding significantly more. Each of the claimed limitations either expand upon or add either 1) new mental process, 2) a new additional element, 3) previously presented mental process, and/or 4) a previously presented additional element.
For example, in claim 32, the additional limitations of “displaying a comparison of the first energy usage and the second energy usage with the recommendation on a display of the user device” is recited at a high level of generality and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. The Federal Circuit in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere displaying of data is a well understood, routine, and conventional function.
As such, claims 1-4, 6-11, 13-18, 20, 29, 30, and 32 are rejected under 35 USC 101 as being drawn to an abstract idea without significantly more, and thus are 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.
Claim(s) 1-4, 6-11, 13-18, 20, 29, 30, and 32 are rejected under 35 U.S.C. 103 as being unpatentable over Grokop, US 2015/0233718 A1, hereinafter referred to as Grokop, in view of GAWRILOW, US 2017/0016730 A1, hereinafter referred to as GAWRILOW, and further in view of Baglino et al., US 2017/0030728 A1, hereinafter referred to as Baglino, respectively.
As to claim 1, Grokop teaches a method performed by a user device, the method comprising:
accessing sparse location data indicative of one or more geographic locations along a route of the user device during a first time period, the route including a starting location data point and an ending location data point (see at least paragraphs 54-57 regarding the system detects the start and end of a drive. An exemplary high-level system overview is shown in flowchart 400 of FIG. 4. During a detected drive the system collects continuous raw accelerometer data 410 and fragmentary GPS data 420. The fragmentary GPS data 420 refers to GPS data being collected only periodically, or at brief segments, rather than continuously throughout the drive. Speed and position values may be obtained from the GPS data. This data is fused at sensor fusion step 430 to estimate G-forces 440 along three axes relative to the vehicle's frame of reference: longitudinal, lateral and vertical. Flags 450 for segments of data that are unusable due to known inaccuracies (such as device movement in the user's hand) are also computed. The fragmentary GPS data 420 is also used to infer a route based on road geometry data 460. See also at least FIGS. 11-12 and paragraphs 137-148 regarding by collecting GPS data continuously throughout a drive, the route driven can be plotted on a map as a sequence of location fixes. A route 1100 having a start point "S" and end point "E", where events 1101, 1102, 1103 and 1104 are associated with precise locations on the route 1100 using dead reckoning, Grokop), the first sparse location data corresponding to a first trip along the route (see at least paragraphs 54-57. See also at least paragraphs 137-148 and 175, Grokop);
accessing motion data collected by one or more sensors of the user device, the motion data collected by the one or more sensors during the first time period (see at least paragraph 54 regarding the system detects the start and end of a drive. An exemplary high-level system overview is shown in flowchart 400 of FIG. 4. During a detected drive the system collects continuous raw accelerometer data 410 and fragmentary GPS data 420. The fragmentary GPS data 420 refers to GPS data being collected only periodically, or at brief segments, rather than continuously throughout the drive. Speed and position values may be obtained from the GPS data. This data is fused at sensor fusion step 430 to estimate G-forces 440 along three axes relative to the vehicle's frame of reference: longitudinal, lateral and vertical. Flags 450 for segments of data that are unusable due to known inaccuracies (such as device movement in the user's hand) are also computed. The fragmentary GPS data 420 is also used to infer a route based on road geometry data 460. See also at least FIGS. 11-12 and paragraphs 137-148. See also at least paragraphs 168-181, Grokop);
accessing road segment information (see at least paragraphs 138-140 regarding by collecting GPS data continuously throughout a drive, the route driven can be plotted on a map as a sequence of location fixes. The speed estimates computed in the previous block 511 can be fused with the route driven (as defined by road geometry) to produce estimates of the location of the user at each sample time, with respect to the road geometry. See also at least paragraphs 152-159 regarding once a set of GPS location fixes has been flagged for being pinned to the route, the problem becomes correctly associating each fix with the road segment on which it occurred, as once the correct road segment is identified each flagged fix can simply be pinned to the nearest point on the segment. Real time dead reckoning analysis can be used to better pin GPS data to a drive route. For instance, if the driving route has been determined for a drive up to a given GPS fix, this last fix can be pinned to the map such that it bests continues the determined route. To do this, the accelerometer sensor measurements may be used to monitor significant changes in driving direction (e.g. has the vehicle turned left/right, started driving in reverse, etc.). These additional checks can be reflected in the cost associated with the different possible road segments for the next fix, Grokop); and
after a conclusion of the first time period, generating, using the sparse location data and the motion data, a dense data set to reconstruct a route, an alignment of the dense data set between the starting location data point and the ending location data point based at least in part on the sparse location data, the motion data, and the road segment information (see at least paragraph 54. See also at least FIGS. 11-12 and paragraphs 137-148. See also at least paragraphs 152-159 regarding once a set of GPS location fixes has been flagged for being pinned to the route, the problem becomes correctly associating each fix with the road segment on which it occurred, as once the correct road segment is identified each flagged fix can simply be pinned to the nearest point on the segment. Real time dead reckoning analysis can be used to better pin GPS data to a drive route. For instance, if the driving route has been determined for a drive up to a given GPS fix, this last fix can be pinned to the map such that it bests continues the determined route. To do this, the accelerometer sensor measurements may be used to monitor significant changes in driving direction (e.g. has the vehicle turned left/right, started driving in reverse, etc.). See also at least FIGS. 18A-20B and paragraphs 168-181 regarding 1) location fixes must be collected only during the route, not at other, superfluous times, and 2) fixes must be obtained sparsely throughout the route. When the monitoring state is entered, location fixes may be obtained with a fixed periodicity of say 1 minute, or with a periodicity that is modulated, say between 30 seconds-5 minutes. The periodicity may be selected based on several factors such as vehicle speed, a route prediction, etc., in order to obtain a more accurate interpolation with fewer samples. At the end of the trip, the fixes are interpolated using a driving directions database. The database may have an API that when queried with a series of fixes, interprets the first and last fixes as the start and end of the route, respectively, and fixes in between as desired waypoints visited by the user. … The algorithm builds a route interpolation API from a driving directions API. The goal of the algorithm is to find a subset of waypoints that when fed into the driving directions API return the route both consistent with the location fixes observed and with the shortest possible length (or quickest drive time). This is illustrated in diagram 191 of FIG. 19A, 192 of FIG. 19B, and 193 of FIG. 19C, which show an exemplary goal of the route interpolation algorithm. Goal of route interpolation algorithm. The assumption here is that the driver took the most direct (or quickest) route consistent with the observed location fixes. Though route 191 of FIG. 19A is shortest, it is not consistent with the location fixes observed and is hence invalid. The route 192 of FIG. 19B is consistent but is unnecessarily long. The route 193 of FIG. 19C is the desired output, as it is the shortest consistent route. The procedure starts with the first and last fix obtained during the drive, (which may for various reasons be the most accurate ones obtained). … From the set of intermediate location fixes that are not sufficiently close to the return drive route, a "best" location fix is selected and added to the set of anchor points. The anchor points are ordered chronologically according to the time the respective location fixes were obtained. The set of anchor points is then again sent to the directions API, with the first anchor point representing the start point of the drive, the last anchor point representing the end point of the drives, and the intermediate location fix representing a waypoint. The waypoint represents a detour in the shortest (or quickest) route between the start and end location. … The last route returned by the directions API will also correspond to this final set of anchor points and hence be used as the inferred driving route, Grokop).
Grokop does not explicitly teach accessing road segment information from a map application based at least in part on accessing the sparse location data and accessing the motion data; or storing the reconstructed route in a local memory of the user device.
However, GAWRILOW teaches accessing road segment information from a map application based at least in part on accessing the sparse location data and accessing the motion data (see at least paragraphs 40-44 regarding the navigation device may comprise a display for displaying the electronic map to a user, a set of one or more processors configured to access the electronic map data and cause the electronic map to be displayed to a user via the display. Means for using the obtained data indicative of the polyline in generating a route through the navigable network as represented by the electronic map, wherein the generated route provides a reconstruction of the route represented by the polyline in relation to the electronic map, and wherein the generating of the route comprises favouring segments of the electronic map for inclusion in the generated route that are in greater proximity to the polyline as represented on the electronic map. See also at least paragraph 154 regarding the system includes a navigation device 300, which can be in the form of a PND or an integrated in-vehicle device. The navigation device stores electronic map data having a plurality of segments representing navigable segments of a navigable network in a given area (map database 305). See also at least FIGS. 7-8C and paragraphs 183-186 regarding FIG. 8A illustrates such data 700 representative of a journey between points A and B. FIG. 8B illustrates a route 710 that may be generated in this way through a navigable network represented by an electronic map made up of segments 720 superimposed on the positional data 700); and storing the reconstructed route in a local memory of the user device (see at least paragraph 68. See also at least Claim 15 regarding storing data indicative of a plurality of routes previously travelled by the device through the navigable network in the area covered by the electronic map of the device, and, for each route, using the previously travelled route data to generate data indicative of a polyline representative of the route, using the obtained data indicative of a polyline to generate a route through the navigable network as represented by the electronic map, the generated route providing a reconstruction of the route represented by the polyline, and storing data indicative of the reconstructed route).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the system of GAWRILOW which teaches accessing road segment information from a map application based at least in part on accessing the sparse location data and accessing the motion data; and storing the reconstructed route in a local memory of the user device with the system of Grokop as both systems are directed to a system and method for reconstructing the route based on the previously travelled route data, and one of ordinary skill in the art would have recognized the established utility of accessing road segment information from a map application based at least in part on accessing the sparse location data and accessing the motion data; and storing the reconstructed route in a local memory of the user device and would have predictably applied it to improve the system of Grokop.
Grokop, as modified by GAWRILOW, does not explicitly teach determining first energy usage for the first trip along the route, the first energy usage based at least in part on one or more driving parameters for the first trip along the route; determining second energy usage for a simulated trip along the route, the second energy usage based at least in part on one or more adjusted driving parameters, the one or more adjusted driving parameters being adjusted from the one or more driving parameters; or determining to generate a recommendation for improving driving efficiency based at least in part on the first energy usage and the second energy usage.
However, Baglino teaches determining first energy usage for the first trip along the route, the first energy usage based at least in part on one or more driving parameters for the first trip along the route (see at least paragraph 16 regarding after the vehicle has driven one or more of the segments, a hindsight energy consumption for the trip so far can then be calculated. In a sense, the hindsight energy calculation represents the energy consumption that would have been predicted at the outset of the trip had the driver's actual speed on the traversed segment(s) been known. The hindsight energy is summed over the number of segments traversed. See also at least FIG. 8B and paragraphs 87-92 regarding the path 818 has an actual component 818A and a predicted component 818B. The actual component reflects the vehicle's actual energy status during the trip so far (i.e., from the start value to the value 820). The predicted component reflects the dynamically updated estimation for the rest of the trip, taking into account the actual energy values so far. That is, based on the dynamic calculation a new end value 824 has now been determined, which represents a downward adjustment (to 5% remaining energy), compared to the previously predicted end value); determining second energy usage for a simulated trip along the route, the second energy usage based at least in part on one or more adjusted driving parameters, the one or more adjusted driving parameters being adjusted from the one or more driving parameters (see at least FIG. 8C and paragraphs 90-94 regarding assuming now that the driver activates the what-if scenario. Particularly, the driver specifies 55 mph as the driving style for the remaining miles, and that climate control will be turned off. Based on the driver's entered information, the prediction is recalculated and the what-if scenario is presented. A simulation path 828 that is provided in such a what-if scenario. The simulation path runs from the value 820 (where the what-if scenario was calculated) to a simulated end point 830. A simulation energy indicator 832 shows that the battery is predicted to have 20% energy remaining at the destination. The simulation path and the simulation energy indicator have dashed outlines to indicate that they are simulations. An area 834 informs the driver that the what-if scenario involves keeping the vehicle speed at 55 mph and turning off climate control. The simulation path 828 is an example of an energy-versus-distance measure); and determining to generate a recommendation for improving driving efficiency based at least in part on the first energy usage and the second energy usage (see at least paragraph 24 regarding the system can present actionable efficiency tips 134 in a user interface 136. For example, the system can recommend that the vehicle be driven more efficiently (such as at lower speed or with less acceleration), that the driver turn off features that consume electric power (e.g., a climate control system) or that the driver close the sunroof or another vehicle closure (which can improve aerodynamics). See also at least FIGS 8A-8C and paragraphs 63-94).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the system of Baglino which teaches determining first energy usage for the first trip along the route, the first energy usage based at least in part on one or more driving parameters for the first trip along the route; determining second energy usage for a simulated trip along the route, the second energy usage based at least in part on one or more adjusted driving parameters, the one or more adjusted driving parameters being adjusted from the one or more driving parameters; and determining to generate a recommendation for improving driving efficiency based at least in part on the first energy usage and the second energy usage with the system of Grokop, as modified by GAWRILOW, as both systems are directed to a system and method for analyzing vehicle travel data to evaluate driving behavior, and one of ordinary skill in the art would have recognized the established utility of determining first energy usage for the first trip along the route, the first energy usage based at least in part on one or more driving parameters for the first trip along the route; determining second energy usage for a simulated trip along the route, the second energy usage based at least in part on one or more adjusted driving parameters, the one or more adjusted driving parameters being adjusted from the one or more driving parameters; and determining to generate a recommendation for improving driving efficiency based at least in part on the first energy usage and the second energy usage and would have predictably applied it to improve the system of Grokop as modified by GAWRILOW.
As to claim 2, Grokop teaches wherein the method further comprises: accessing road network data based on the one or more geographic locations along the route, the road network data representing a plurality of road segments of a road network (see at least paragraph 54 regarding the fragmentary GPS data 420 is also used to infer a route based on road geometry data 460. See also at least FIGS. 10A-14 and paragraphs 137-140 and 158 regarding by collecting GPS data continuously throughout a drive, the route driven can be plotted on a map as a sequence of location fixes, Grokop), wherein the generating, using the sparse location data and the motion data, the dense data set to reconstruct the route further comprises using the road network data to reconstruct the route (see at least paragraph 54. See also at least FIGS. 11-12 and paragraphs 137-148. See also at least FIGS. 18A-20B and paragraphs 168-181, Grokop).
As to claim 3, Grokop teaches wherein the accessing the sparse location data comprises: accessing the sparse location data from an application operating on the user device (see at least paragraphs 168-181 regarding in order to use location fixes to retroactively learn a drive route that was taken by a mobile device, without severely impacting battery life or accuracy, two things must happen: 1) location fixes must be collected only during the route, not at other, superfluous times, and 2) fixes must be obtained sparsely throughout the route. The algorithm builds a route interpolation API from a driving directions API, Grokop).
As to claim 4, Grokop teaches wherein the method further comprises: storing the sparse location data in the local memory of the user device during the first time period, wherein the sparse location data is accessed from the local memory of the user device (see at least paragraphs 54-57 and 205 regarding the system detects the start and end of a drive. An exemplary high-level system overview is shown in flowchart 400 of FIG. 4. During a detected drive the system collects continuous raw accelerometer data 410 and fragmentary GPS data 420. The fragmentary GPS data 420 refers to GPS data being collected only periodically, or at brief segments, rather than continuously throughout the drive. Speed and position values may be obtained from the GPS data. This data is fused at sensor fusion step 430 to estimate G-forces 440 along three axes relative to the vehicle's frame of reference: longitudinal, lateral and vertical. During a drive, the following occurs. When a drive start is detected, the system starts continuously logging raw accelerometer data until the drive end has been detected. For example, F.sub.S=20-200 accelerometer data vectors are logged per second, where F.sub.S is the sampling rate. The continuous accelerometer data is subdivided into frames of width 1/F.sub.G where F.sub.G represents the rate at which movement quantities are outputted (in samples per sec). Thus, a frame is a quantity of time in which a sample data point is taken. The subdividing into frames can occur during collection of the data, or after the drive is completed. An exemplary range for F.sub.G is 1-10 Hz, which would correspond to frames of 1 second to 0.1 sec. From each frame, sufficient statistics are computed and stored for later processing, Grokop).
As to claim 6, Grokop teaches wherein the method further comprises: accessing road network data based on the sparse location data, the road network data representing a plurality of road segments of a road network (see at least paragraph 54 regarding the fragmentary GPS data 420 is also used to infer a route based on road geometry data 460. See also at least FIGS. 19A-20B and paragraphs 137-148 and 158 regarding by collecting GPS data continuously throughout a drive, the route driven can be plotted on a map as a sequence of location fixes, Grokop);
determining a first road segment that connects to a second road segment, the first road segment corresponding to a first sparse location data point of the sparse location data, the second road segment corresponding to a second sparse location data point of the sparse location data, and the first road segment and the second road segment corresponding to the route (see at least FIGS. 19A-20B and paragraphs 168-181 regarding the anchor points are ordered chronologically according to the time the respective location fixes were obtained. The set of anchor points is then again sent to the directions API, with the first anchor point representing the start point of the drive, the last anchor point representing the end point of the drives, and the intermediate location fix representing a waypoint. The waypoint represents a detour in the shortest (or quickest) route between the start and end location. This procedure is recursively repeated, such as in diagram 2050, on remaining segments of the route that contain points yet to be designated either anchor or ignore points. When all location fixes have been labeled either anchor or ignore points, the procedure terminates, Grokop), wherein generating the reconstructed route is based at least in part on the first road segment and the second road segment (see at least FIGS. 19A-20B and paragraphs 168-181 regarding the anchor points are ordered chronologically according to the time the respective location fixes were obtained. The set of anchor points is then again sent to the directions API, with the first anchor point representing the start point of the drive, the last anchor point representing the end point of the drives, and the intermediate location fix representing a waypoint. The waypoint represents a detour in the shortest (or quickest) route between the start and end location. This procedure is recursively repeated, such as in diagram 2050, on remaining segments of the route that contain points yet to be designated either anchor or ignore points. When all location fixes have been labeled either anchor or ignore points, the procedure terminates. The final set of anchor points is considered a minimal set of location fixes necessary to characterize the route, including its start and end points, and any detours. The last route returned by the directions API will also correspond to this final set of anchor points and hence be used as the inferred driving route, Grokop).
As to claim 7, Grokop teaches wherein the determining the first road segment comprises evaluating the first sparse location data point with respect to a first proximity parameter, and wherein the determining the second road segment comprises evaluating the second sparse location data point with respect to a second proximity parameter (see at least paragraphs 137-140 regarding the speed estimates computed in the previous block 511 can be fused with the route driven (as defined by road geometry) to produce estimates of the location of the user at each sample time, with respect to the road geometry. That is, vehicle position can be estimated by fusing the vehicle speed estimates with route and road geometry information. As the system produces these estimates by turning the GPS on for only a small fraction of the drive, this approach provides a precise location history of the user with little energy consumed. This process is referred to as dead reckoning. A route taken by the vehicle is computed using the estimated vehicle positions and the road geometry information. The position of the vehicle is interpolated during segments of time in which position data is not collected on the mobile device, using the vehicle speed estimates, the estimated vehicle positions, and the computed route taken by the vehicle. Interpolating the position of the vehicle can include finding points on the computed route associated with each interpolated position, and interpolating the distance of the vehicle along the route, between the found points. The route driven can be computed with the aid of road geometry using the techniques described in section "Inferring a drive route from sparse location fixes using a driving directions AP". This corresponds to the "Compute route using road geometry block" 513 in FIG. 5. The output of this block is a sequence of latitudinal/longitudinal coordinates that represent the start and end points of each segment of the route. This is a piecewise longitudinal representation of the underlying road geometry. This is illustrated in FIGS. 10A-10B, showing two examples of sequential latitudinal/longitudinal coordinates, shown as open circles in the figures, that represent the start and end points of each segment of the route, Grokop).
As to claim 8, Examiner notes claim 8 recites similar limitations to claim 1 and is rejected under the same rational.
As to claim 9, Examiner notes claim 9 recites similar limitations to claim 2 and is rejected under the same rational.
As to claim 10, Examiner notes claim 10 recites similar limitations to claim 3 and is rejected under the same rational.
As to claim 11, Examiner notes claim 11 recites similar limitations to claim 4 and is rejected under the same rational.
As to claim 13, Examiner notes claim 13 recites similar limitations to claim 6 and is rejected under the same rational.
As to claim 14, Examiner notes claim 14 recites similar limitations to claim 7 and is rejected under the same rational.
As to claim 15, Examiner notes claim 15 recites similar limitations to claim 1 and is rejected under the same rational.
As to claim 16, Examiner notes claim 16 recites similar limitations to claim 2 and is rejected under the same rational.
As to claim 17, Examiner notes claim 17 recites similar limitations to claim 3 and is rejected under the same rational.
As to claim 18, Examiner notes claim 18 recites similar limitations to claim 4 and is rejected under the same rational.
As to claim 20, Examiner notes claim 20 recites similar limitations to claim 6 and is rejected under the same rational.
As to claim 29, Grokop does not explicitly teach displaying the reconstructed route overlayed on a road network displayed by the map application, the reconstructed route beginning at the starting location data point and ending at the ending location data point.
However, such matter is taught by GAWRILOW (see at least paragraphs 4 and 14-15 regarding during navigation along a calculated route, it is usual for such PNDs to provide visual and/or audible instructions to guide the user along a chosen route to the end of that route, i.e. the desired destination. It is also usual for PNDs to display map information on-screen during the navigation, such information regularly being updated on-screen so that the map information displayed is representative of the current location of the device, and thus of the user or user's vehicle if the device is being used for in-vehicle navigation. See also at least paragraphs 137-139. See also at least paragraphs 154-165 regarding once the navigation device has reconstructed the route in relation to its own electronic map data, it may use the route in any suitable manner, and may display the route and/or generate a set of navigation instructions to guide a user along the route).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the system of GAWRILOW which teaches displaying the reconstructed route overlayed on a road network displayed by the map application, the reconstructed route beginning at the starting location data point and ending at the ending location data point with the system of Grokop as both systems are directed to a system and method for reconstructing the route based on the previously travelled route data, and one of ordinary skill in the art would have recognized the established utility of displaying the reconstructed route overlayed on a road network displayed by the map application, the reconstructed route beginning at the starting location data point and ending at the ending location data point and would have predictably applied it to improve the system of Grokop.
As to claim 30, Examiner notes claim 30 recites similar limitations to claim 29 and is rejected under the same rational.
As to claim 32, Grokop, as modified by GAWRILOW, does not explicitly teach displaying a comparison of the first energy usage and the second energy usage with the recommendation on a display of the user device.
However, such matter is taught by Baglino (see at least FIGS. 7A-8C and paragraphs 57-94 regarding whether or not the driver has run any what-if scenario in the system (indeed, whether the particular implementation offers that ability or not), the system can provide recommendations to the driver, for example as illustrated in FIG. 7C. For example, assume that the indicator 312 for the Bakersfield charging waypoint currently reads 5%. This would mean that the value has decreased from the earlier predicted level (see, e.g., FIG. 7A) during driving. … at least one of the recommendations 712A-B can also be (or include) a control to effectuate the same recommendation. For example, the driver can click the recommendation 712B to trigger the vehicle's control system to close the sunroof. Of course, the driver could instead effectuate any such recommendation in the regular way the change is made—by driving slower, closing the sunroof or turning off the climate control, to name just a few examples).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the system of Baglino which teaches displaying a comparison of the first energy usage and the second energy usage with the recommendation on a display of the user device with the system of Grokop, as modified by GAWRILOW, as both systems are directed to a system and method for analyzing vehicle travel data to evaluate driving behavior, and one of ordinary skill in the art would have recognized the established utility of displaying a comparison of the first energy usage and the second energy usage with the recommendation on a display of the user device and would have predictably applied it to improve the system of Grokop as modified by GAWRILOW.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
LIN (WO 2024082201 A1) regarding a system for determining the predicted energy consumption based on the simulated driving data obtained by the simulation.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KYLE S. PARK whose telephone number is (571)272-3151. The examiner can normally be reached Mon-Thurs 9:00AM-5:00PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anne M ANTONUCCI can be reached at (313)446-6519. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/K.S.P./Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666
