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 .
This office action is in response to applicant’s arguments/remarks and amendments filed on 07/14/2026. Claims 1, 3, 6, 14, and 15 have been amended. No Claims have been newly cancelled. No Claims have been newly added. Accordingly, claims 1-10, and 12-18 are currently pending.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-10, and 12-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) determining a geographic zone of interest, determining a geographic detection zone, detecting a presence of a plurality of first devices, receiving a plurality of first report signals, determining one or more movement features, calculating one or more predictors, receiving a traffic signal, determining reference data, and storing reference data.
The limitations of “determining a geographic zone of interest, determining a geographic detection zone, detecting the presence of a plurality of first devices, determining one or more movement features, calculating one or more predictors, determining reference data, and storing reference data”, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “a first/second memory, and a first/second processing units,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “a first/second memory, and a first/second processing units” language, “determining, detecting, and calculating” in the context of this claim encompasses the user mentally calculating traffic based on available data using observation, evaluation, judgment, and opinion. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. The claims recite the additional elements of “a first/second memory, and a first/second processing units”. Said elements are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Regarding the additional limitations of “receiving a plurality of first report signals from a corresponding cellular network”, “receiving a traffic signal”, and “receiving a plurality of second report signals”, the examiner submits that these limitations are insignificant extra-solution activities. Said limitations are recited at a high level of generality (i.e. as a general means of gathering data), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. 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.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “a first/second memory, and a first/second processing units” amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The additional limitations of “receiving a plurality of first report signals from a corresponding cellular network”, “receiving a traffic signal”, and “receiving a plurality of second report signals”, are well-understood, routine, and conventional activities. 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 collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner. Hence, the claims are not patent eligible.
Dependent claim(s) 2-5, 7-10, 12-13, and 16-18 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/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. Claims 2-4, 7-10, 12-13, and 16-18 do not include any additional elements integrate the abstract idea into a practical application. Claim 5 recites that the correlation is established using machine learning tool. Said machine learning tool is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Therefore, dependent claims 2-5, 7-10, 12-13, and 16-18 are not patent eligible under the same rationale as provided for in the rejection of independent claims 1 and 6.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 3-6, 8-10, and 12-18 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhao et al US 2017/0309171 A1 (hence Zhao).
In re claims 1 and 14, Zhao discloses using a plurality of probe reports to augment a geographic database with traffic volume data (Abstract) and teaches the following:
generating reference data for traffic condition prediction (Abstract), comprising:
determining a geographic zone of interest (Fig.1, “the roadway network illustrating five segments 91, 92, 93, 94, and 95”, Fig.3, “enlarged map 204 illustrates part of a road network 208 in the geographic region 202“, Fig.7, the plurality of road segments 72-76 constitute the geographic zone of interest);
determining a geographic detection zone, associated to but different from said geographic zone of interest and located along a route to said geographic zone of interest (Fig.7, and Paragraph 0047 “five segments 72, 73, 74, 75, and 76 shown. Each segment is illustrated as approximately ten meters, however, the length of the segments may vary”);
detecting a presence of a plurality of first devices in said geographic detection zone, said first devices being mobile user terminals (Paragraphs 0006 “one or more vehicles”, Paragraph 0047 “There is an additional probe vehicle 79 located in segment 72 that also will generate a report”, and Paragraph 0057);
for each device of said first devices: receiving over time a plurality of first report signals from a corresponding cellular network, each report signal including: a geographical position of said each first device, a time reference associated with said geographical position and at least one of a user-related identifier and a session identifier, such that time references and geographical positions are received for all of said first devices (Fig.7, and Paragraphs 0040, 0043, 0047, and 0050);
based on said first report signals, determining one or more movement features correlated to movement of said each first device in said geographic detection zone, such that one or more movement features are determined for all of said first devices (Paragraphs 0046-0047, Paragraph 0052 “a probe probability value”, and Paragraphs 0064-0065);
based on said one or more movement features of all said first devices, calculating one or more predictors, associated to said time references and said geographical positions received for all of said first devices (Paragraphs 0027, 0029, “estimate traffic volume on one or more road segments”, Paragraphs 0039 and 0041, “The server 125 may also provide historical, future, recent or current traffic conditions for the links, segments, paths, or routes using historical, recent, or real time collected data”, and Paragraphs 0048, 0071, and 0075);
receiving a traffic signal, representative of a traffic condition in said geographic zone of interest, said traffic condition having occurred after a determined time with respect to said one or more of time references determined for all of said first devices (Paragraph 0073 “Events may also be taken into consideration when the server 125 calculates current traffic volume estimates.”, Paragraph 0075 “make predictions based on known data to adjust or calibrate the traffic volume model”, and Paragraph 0076 “Actual volume data collected using roadside sensors 1023 may be used to train the traffic volume model”);
determining reference data, based on said calculated predictors and said traffic condition, for correlating said predictors and said traffic condition (Paragraphs 0075-0077, “Machine learning may make predictions based on data from roadside sensors 1023 with regression methods”, and “The traffic volume model may be used to estimate traffic volume for a segment and a time period”);
and storing said reference data in a first memory (Paragraph 0079)
With respect to claims 6 and 15, Zhao teaches the following:
predicting traffic conditions (Abstract), comprising:
determining a geographic zone of interest (Fig.1, “the roadway network illustrating five segments 91, 92, 93, 94, and 95”, Fig.3, “enlarged map 204 illustrates part of a road network 208 in the geographic region 202“, Fig.7, the plurality of road segments 72-76 constitute the geographic zone of interest);
determining a geographic detection zone, associated to but different from said geographic zone of interest and located along a route to said geographic zone of interest (Fig.7, and Paragraph 0047 “five segments 72, 73, 74, 75, and 76 shown. Each segment is illustrated as approximately ten meters, however, the length of the segments may vary”);
providing, in a memory, reference data, said reference data correlating predictors associated to possible movement features of mobile devices in said geographic detection zone at a first time with possible traffic conditions in said geographic zone of interest at a second time, said second time occurring after a determined time with respect to said first time (Paragraphs 0075-0077, “Machine learning may make predictions based on data from roadside sensors 1023 with regression methods”, and “The traffic volume model may be used to estimate traffic volume for a segment and a time period”, and Paragraph 0079);
detecting the presence of a plurality of second devices in said geographic detection zone, said second devices being mobile user terminals (Paragraphs 0006 “one or more vehicles”, Paragraph 0047 “There is an additional probe vehicle 79 located in segment 72 that also will generate a report”, and Paragraph 0057);
for each of said second devices: receiving over time a plurality of second report signals from a corresponding cellular network, each second report signal including: a geographical position of said second device, a time reference associated with said geographical position and at least one of a user-related identifier and a session identifier (Fig.7, and Paragraphs 0043, 0047, and 0050);
based on said second report signals, determining one or more movement features correlated to movement of said second device in said geographic detection zone (Paragraphs 0040, 0046-0047, Paragraph 0052 “a probe probability value”, and Paragraphs 0064-0065);
based on said one or more movement features of said second devices, calculating detection data corresponding to said predictors, associated to said time references and said geographical positions (Paragraph 0064);
processing said detection data based on said reference data, obtaining a prediction of a traffic condition in said geographic zone of interest for a time occurring after a determined time with respect to the time references included in said second report signals (Paragraphs 0075-0077, “Machine learning may make predictions based on data from roadside sensors 1023 with regression methods”, and “The traffic volume model may be used to estimate traffic volume for a segment and a time period”, and Paragraph 0079); and
generating a data signal representative of said predicted traffic condition (Paragraph 0080)
In re claims 3, and 8, Zhao teaches the following:
wherein said one or more movement features include a trajectory along which said each first/second device moves and/or the speed at which each said first/second device moves in said geographic detection zone (Fig.7 and Paragraph 0047)
In re claims 4, and 10, Zhao teaches the following:
wherein said one or more predictors comprise one or more of the following: an average speed of said first devices; and a variance of the speed of said first devices (Paragraph 0047)
In re claim 5, Zhao teaches the following:
wherein the correlation between said one or more predictors and possible traffic conditions in said geographic zone of interest is established via a machine learning tool (Paragraphs 0059 and 0075)
In re claim 9, Zhao teaches the following:
wherein possible traffic conditions in said geographic zone of interest are represented by two or more labels, wherein obtaining a prediction of the traffic condition comprises selecting a label of said two or more labels (Paragraph 0033)
In re claim 12, Zhao teaches the following:
at least one of the following: sending said data signal to a display installed in an area associated with said geographic detection zone; sending said data signal to mobile devices in said geographic detection zone; and sending said data signal to a traffic management system associated with said geographic detection zone and/or with said geographic zone of interest (Paragraphs 0080-0085)
In re claim 13, Zhao teaches the following:
determining a suggested speed for mobile devices in the geographic detection zone; and including said suggested speed in said data signal (Paragraph 0080)
In re claim 16, Zhao teaches the following:
wherein the geographic zone of interest and the geographic detection zone are spaced apart (Fig.1 and Paragraph 0023)
In re claim 17, Zhao teaches the following:
wherein the geographic zone of interest and the geographic detection zone overlap (Fig.3, and Paragraph 0029)
In re claim 18, Zhao teaches the following:
wherein the geographic zone of interest is within the geographic detection zone (Fig.7, and Paragraph 0047)
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 2 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhao in view of Persson et al US 9,877,220 B2 (hence Persson).
In re claims 2 and 7, Zhao discloses the claimed invention as recited above but doesn’t explicitly teach the following:
wherein said first report signals are Minimization of Drive Test, MDT, signals or are generated based on MDT signals
Nevertheless, Persson discloses mechanisms for network based control of report messages comprising logged measurements in a wireless communications network (Abstract) and teaches the following:
wherein said first report signals are Minimization of Drive Test, MDT signals or are generated based on MDT signals (Col.5, lines 43-53)
It would have been obvious to one having ordinary skills in the art at the time the invention was filed to have modified the Zhao reference to include MDT signals of MDT log reports, as taught by Persson, with a reasonable expectation of success, as an example of received logged measurements (Persson, Abstract).
Response to Arguments
Applicant's arguments filed on 07/14/2026 have been fully considered but they are not persuasive.
With respect to applicant’s arguments/remarks with respect to the rejection of claims 1-10 and 12-15 under 35 U.S.C. 101 and that the step of receiving first report signal from a corresponding cellular network cannot be performed in the human mind, and is an integral part of the solution to the problem, the examiner respectfully disagrees with that statement. As recited above, the step of receiving first report signal from a corresponding cellular network is not considered part of the mental process. It is analyzed as an additional element that is insignificant extra-solution activities. Said limitations is recited at a high level of generality (i.e. as a general means of gathering data), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The additional limitations of “receiving a plurality of first report signals from a corresponding cellular network”, is well-understood, routine, and conventional activities. 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 collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner.
With respect to applicant’s arguments/remarks with respect to the rejection of claims 1-10 and 12-15 under 35 U.S.C. 101 and that this claimed ordered combination provides a specific technique that improves the technological field of traffic condition modeling and that the claims integrate any alleged abstract idea into a practical application, the examiner respectfully disagrees with that statement. As discussed above, the recited steps are not directed to a specific improvement in how a server or a computer works in order to process data to estimate traffic, i.e. it is not the incorporation of the claimed rules that improves the existing technological process. The claims here are implementing on old process of data computation in a new environment, i.e. an abstract idea implemented on a computer and not an improvement in a way a traffic server or computer operates. 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.
With respect to applicant’s arguments/remarks with respect to the rejection of claims 1, 3-6, 8-10, and 12-15 under 35 U.S.C. 102(a)(1) as being anticipated by Zhao, and Zhao does not disclose or suggest “a geographic detection zone, associated to but different from said geographic zone of interest and located along a route to said geographic zone of interest”, the examiner respectfully disagrees with that statement. As described above, Zhao describes a geographic zone of interest as described in Fig.1 and Paragraph 0023 “a roadway network including multiple road segments” and as shown in Fig.3 and Paragraph 0029 “road network 208”, and “each road in the geographic region 202 is composed of one or more road segments 210”. Accordingly, the road network reads on the geographic zone of interest and each segment reads on the geographic detection zone. Furthermore, and as recited above, Zhao discloses that any of segments 73-76, when picked, would read on the geographic zone of interest and any of segments 72-75 would read on a geographic detection zone. For example, if segment 76 is designated as the geographic zone of interest, at least segment 72 would read on “a geographic detection zone, associated to but different from said geographic zone of interest and located along a route to said geographic zone of interest”.
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 RAMI KHATIB whose telephone number is (571)270-1165. The examiner can normally be reached M-F: 9:00am-5:30pm.
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, Erin M Piateski can be reached at 571-270 7429. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RAMI KHATIB/Primary Examiner, Art Unit 3669
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