DETAILED ACTION
This FINAL action is responsive to the amendment filed 5/15/2026 and IDS filed 4/22/2026.
In the application Claims 1-20 remain pending. Claims 1, 13 and 17 are the independent claims.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
4. The information disclosure statement (IDS) submitted on 4/22/2026 has been entered, and considered by the examiner.
Withdrawn Objections
5. The objection to claim 3 has been withdrawn in light of the amendment.
Withdrawn Rejections
6. The 35 U.S.C. 112(b) rejection of claims 13-20 have been withdrawn in light of the amendment.
7. The 35 U.S.C. 103 rejection of claims 1-2 and 6-12 with cited references of Liang (U.S. Pub 2019/0138024) in view of Lee (U.S. 8,306,940) has been withdrawn in light of the amendment.
8. The 35 U.S.C. 103 rejection of claims 13 and 17-18 with cited reference of Liang (U.S. Pub 2019/0138024) has been withdrawn in light of the amendment.
Difference over Prior art
9. The cited reference of Liang (U.S. Pub 2019/0138024) teaches processing overhead imagery using CV and ML models to classify lane attribute including the DoT, generating prediction scores (confidence values) and aligning classification results with lane geometry and storing the resulting lane attributes in a geographic database for navigation. However, Liang fails to teach determining the DoT from a plurality of independently detected features that each provide a candidate direction, applying weighted voting mechanism to reconcile the candidate directions, weighting votes based on feature type or associating identical detected features to lane geometry based on their geospatial relationship.
10. The cited reference of Lee (U.S. 8,306,940) teaches combining outputs of multiple trained classifiers using weighted linear combinations of confidence-like scores to produce an ensemble classification. Lee however is unrelated to overhead imagery, road networks, lane direction determination or geographic databases. In addition, failing to disclose weighting based on detected roadway feature types, automatically weighting dynamically detected features at inference time, using a voting mechanism where detected features cast candidate-direction votes, associating detected features to lane geometry through geospatial relationships or storing the determined lane attribute in a geographic database.
Claim Rejections - 35 USC § 101
11. 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.
12. Claim 1-20 remain rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. abstract idea) without significantly more.
The determination of whether a claim recites patent ineligible subject matter is a 2-step inquiry.
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), see MPEP 2106.03, 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: see MPEP 2106.04
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon? see MPEP 2106.04(II)(A)(1)
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? see MPEP 2106.04(II)(A)(2) and 2106.05(a) thru (d) for explanations.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? see MPEP 2106.05
101 Analysis – Step 1
Claim 1 is directed to “A method” (process). Claim 13 is directed to “An apparatus comprising:” (machine). Claim 17 is directed to “A non-transitory computer readable storage medium” (composition of matter). Therefore, the claims are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis, 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. see MPEP 2106(A)(II)(1) and MPEP 2106.04(a)-(c)
Independent claims 1, 13 and 17 includes limitations that recite an abstract idea (emphasized below [with the category of abstract idea in brackets]).
Claim 1, A method comprising:
processing overhead imagery data of a road network to determine a plurality of features indicative of a direction of travel of at least one road lane of the road network, wherein each feature of the plurality of features indicates a candidate direction of travel, [MPEP 2106.05(g) Insignificant Extra-Solution Activity, data gathering, pre-solution activity];
wherein determining the plurality of features comprises applying one or more computer-vision or machine learning models to detect the plurality of features from the overhead imagery and to output, for each detected feature, a confidence value [MPEP 2106.05(f) Mere Instructions to Apply an Exception] & [MPEP 2106.05(h) Field of Use and Technological Environment] & [MPEP 2106.05(g) Insignificant Extra-Solution Activity, data gathering, pre-solution activity];
associating each detected feature with the at least one road lane based on a geospatial relationship between the detected feature and a lane geometry of the at least one road lane [mathematical concept] & [mental process];
determining the direction of travel of the at least one road lane based on a weighted voting mechanism [mental process] & [mathematical concept];
applied based on the candidate direction of travel of each feature [MPEP 2106.05(f) Mere Instructions to Apply an Exception],
wherein the weighted voting mechanism weighs the candidate direction of travel of each feature based on a feature type of each feature, and further based on the confidence value for each detected feature [mathematical concept]; and
associating the determined direction of travel as an attribute of the at least one road lane in a geographic database [MPEP 2106.05(g) Insignificant Extra-Solution Activity, post-solution activity].
Claim 13, An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to:
process overhead imagery data of a road network to determine a plurality of features, indicative of a direction of travel of at least one road lane of the road network, [MPEP 2106.05(g) Insignificant Extra-Solution Activity, data gathering, pre-solution activity];
wherein processing comprises applying one or more computer-vision or machine-learning models to detect the plurality of features and to output, for each detected feature a confidence value [MPEP 2106.05(f) Mere Instructions to Apply an Exception] & [MPEP 2106.05(h) Field of Use and Technological Environment] & [MPEP 2106.05(g) Insignificant Extra-Solution Activity, data gathering, pre-solution activity];
associated each detected feature with the at least one road lane based on geospatial relationship between the detected feature and a lane geometry of the at least one road lane [mathematical concept] & [mental process];
determine a pattern of features from the plurality of features [mental process];
determine a direction of travel based on the pattern of features [mental process]; and
associate the determined direction of travel as an attribute of the at least one road lane in a geographic database [MPEP 2106.05(g) Insignificant Extra-Solution Activity, post-solution activity].
Claim 17, A non-transitory computer-readable storage medium, carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform:
processing overhead imagery data of a road network to determine one or more features, indicative of a direction of travel of at least one road lane of the road network, wherein processing comprises applying one or more computer-vision or machine-learning models to detect the one or more features and to output, for each detected feature, a confidence value [MPEP 2106.05(g) Insignificant Extra-Solution Activity, data gathering, pre-solution activity] & [MPEP 2106.05(f) Mere Instructions to Apply an Exception] & [MPEP 2106.05(h) Field of Use and Technological Environment];
determining a relative location of each feature of the one or more features to the at least one road lane [mental process];
determining the direction of travel of the at least one road lane based on the relative location [mental process]; and
associating the determined direction of travel as an attribute of the at least one road lane in a geographic database [MPEP 2106.05(g) Insignificant Extra-Solution Activity, post-solution activity].
The Examiner submits that the foregoing bolded limitation(s) above: constitute a “mathematical concept” & “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind.
Claims 1, 13 and 17 recite, determining the direction of travel, determine a pattern of features, determine a relative location of each feature which fall under mental process that involves evaluation/judgement combined with calculations from the voting mechanism. Weighted voting involves mathematical calculations (weights, sums, averages etc.). Determining/identifying features involves observation and evaluation that can be performed by a human analyzing images along with pattern recognition. Evaluating whether a feature indicates direction is a judgement. Each feature being evaluated as a candidate direction involves mental observation and judgement about what the feature suggests. In addition, assigning and applying weights based on feature types involves mathematical calculations and relationships, the weighing function is a mathematical operation. Furthermore, correlating a feature to a lane via proximity/geometry is a geometric calculation that can also be performed mentally or via pen and paper by visually matching a marking to a lane.
Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. see MPEP 2106.04(II)(A)(2) and MPEP 2106.04(d)(2). It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations”, while the bolded portions continue to represent the “abstract idea”.):
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application. Regarding the additional limitations of “processing overhead imagery data” & “associating the determined direction of travel” & “output, for each detected feature, a confidence”. The Examiner submits that the step of processing overhead imagery is a data gathering process that obtains information that feeds into the analysis, which is pre-solution activity. In addition, associating the determined direction of travel amounts to post-solution activity that includes outputting data after the main process which is then stored. Updating stored records (activity log) is insignificant extra-solution activity. The claims further confine the idea to the overhead-imagery mapping field thereby falling under a field of use. Also, the detected feature having an output confidence value is collecting generic output via confidence score from the model which amounts to data gathering.
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, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, 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 – Step 2B
Regarding Step 2B of the Revised Guidance, representative claims 1, 13 and 17 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 “applied based on” & “applying one or more computer-vision or machine learning models to detect the plurality of features”, amounts to applying the voting mechanism via “apply it” with the judicial exception and merely include instructions to implement an abstract idea on a computer that are not integrated into a practical application. The claims further invoke generic CV/ML models as a tool to carry out the mental/mathematical steps without any disclosed improvement to the models themselves.
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above the examiner submits that these limitations are insignificant extra-solution activities. See 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) in addition to -Collecting information, analyzing it, and displaying certain results of the collection and analysis (Electric Power Group), Collecting data, recognizing certain data within the collected data set and storing the recognized data in memory (Content Extraction).
Dependent claims 2-4, 6, 8-9, 12, 14-16 and 19-20, -do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and do not integrate the judicial exception into a practical application. The claims describe features that fall under a mental process that involve observation, inference, judgement and pattern recognition along with mathematical concepts. Therefore, the claims are not patent eligible under the same rationale as provided for in the rejection of the Independent claims. Therefore, the claims are ineligible under 35 USC §101.
Dependent claim 5, -do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and do not integrate the judicial exception into a practical application. The claims describe weighted majority vote which falls under mathematical concepts involving pure math operations. Therefore, the claims are not patent eligible under the same rationale as provided for in the rejection of the Independent claims. Therefore, the claims are ineligible under 35 USC §101.
Dependent claims 7, 10-11 and 18, -do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and do not integrate the judicial exception into a practical application. The claims describe features that fall under [MPEP 2106.05(h) Field of Use and Technological Environment]. Therefore, the claims are not patent eligible under the same rationale as provided for in the rejection of the Independent claims. Therefore, the claims are ineligible under 35 USC §101.
Response to Arguments
13. Applicant’s arguments filed 4/14/2026 has been considered but are not persuasive regarding the 35 U.S.C. 101 abstract idea rejection.
Applicant Argues: The amended claims do not merely “apply” a voting concept; rather they specifically apply confidence-weighted, feature-type-weighted voting to computer-vision-detected features that have been geospatially associated with lane geometry, to determine lane-level DoT and store it as a lane attribute in a geographic database. These limitations are concrete, technical operations described in the specification and are not merely generic computer implementation or insignificant extra-solution activity. (see pgs. 9-10)
The Examiner Respectfully Disagrees: The addition of determining the features via computer vision (CV)/ML models invoke generic models as a tool to carry out the mental/mathematical steps to identify roadway features without any disclosed improvement to the models themselves with the confidence value being data generated by those tools. In addition, associating the detected feature with road lane based on geospatial relationship between the feature and lane geometry of road lanes is correlating a feature to a lane via proximity/geometry is a geometric calculation that can also be performed mentally or via pen and paper by visually matching a marking to a lane. The claims do not recite any improvement to CV technology or ML models, geospatial processing or computer functionality itself. Instead, they use these generic computer technologies as a tool to automate a process that could be otherwise performed by observing roadway features, evaluating their significance, determining a direction of travel and recording the result. The additional elements therefore merely implement the abstract idea on a generic computer environment and therefore do not amount to significantly more than an abstract idea. However, applicant’s specification does provide additional detail that emphasize improvements to digital map creation that may help overcome the cited 35 U.S.C. 101 abstract idea rejection.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MANGLESH M PATEL whose telephone number is (571)272-5937. The examiner can normally be reached on M-F from 10:30 am to 7:30 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erin D. Bishop, can be reached at telephone number 571-270-3713. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Manglesh M Patel/
Primary Examiner, Art Unit 3665
7/29/2026
