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 .
Status of the Claims
This Office Action is in response to the claims filed on January 30, 2026.
Claims 1-10 and 20-29 have been presented for examination.
Claims 1-10 and 20-29 are currently rejected.
Claims 1-10 and 20-29 are rejected under 35 U.S.C. 101.
Claims 1-2, 6, 10, 20-21, 23, and 26-29 are rejected under 35 U.S.C. 103 as being unpatentable over Holder et al. (U.S. Patent Publication Number 2020/0168104) in view of Gu et al. (U.S. Patent Publication Number 2022/0076583), further in view of Chaubey et al. (U.S. Patent Publication Number 2022/0139234).
Claims 3 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Holder et al. (U.S. Patent Publication Number 2020/0168104) in view of Gu et al. (U.S. Patent Publication Number 2022/0076583) and Chaubey et al. (U.S. Patent Publication Number 2022/0139234), further in view of Bombelli (“Strategic Air Traffic Planning with Fréchet Distance Aggregation and Rerouting”).
Claim 24 is rejected under 35 U.S.C. 103 as being unpatentable over Holder et al. (U.S. Patent Publication Number 2020/0168104) in view of Gu et al. (U.S. Patent Publication Number 2022/0076583) and Chaubey et al. (U.S. Patent Publication Number 2022/0139234), further in view of Pang et al. (“Aircraft Trajectory Prediction using LSTM Neural Network with Embedded Convolutional Layer”).
Response to Arguments
35 U.S.C. 112
Claims 11-19 have been cancelled with respect to the claims submitted on January 30, 2026. Accordingly, the 35 U.S.C. 112 rejection is withdrawn.
35 U.S.C. 101
Applicant's arguments filed on January 30, 2026 have been fully considered but they are not persuasive.
The Applicant argues that the limitations of claim 1 require “processing and integration of large-scale, machine generated aviation and meteorological datasets and the generation of spatially correlated probability figures” and cannot practically be performed in the human mind (Applicant Remarks page 12).
The Examiner has considered the arguments presented and respectfully disagrees. Embodiments appearing in the written description may not be read into a claim when the claim language is broader than the embodiment (MPEP 2111.01(II)). The claims do not expressly recite nor do they suggest processing and integration of data at a “large-scale,” nor is “large-scale” processing supported by the specification. Rather, the claims are merely directed to collecting data in real time and acquiring flight information. The “processing and integration” of the data is encompassed by the determining steps, constructing a probability figure, and formulating and providing a strategy, wherein each of these steps may be performed mentally. For example, based on the data that is collected in real-time, a person supervising the data collection may mentally determine the flight route at the airport terminal and determine a likelihood that the flight route requires deviation based on known historical weather data. The person may further construct a simple probability figure and verbally provide a strategy. Therefore, the claims under their broadest reasonable interpretation do not expressly require “large-scale” processing and integration and encompass a mental process that uses data that has been collected and made readily available.
The Applicant argues that the claim is integrated into a practical application because the claimed steps result in an improvement in the technical process for terminal-area flight routing decisions made under convective weather conditions (Applicant Remarks page 12). The Applicant further argues that the collecting and acquiring steps are technical inputs necessary to generate probability figures for formulating flight strategies, and that the computer components define a sequence of operations that “transform aviation and weather data into actionable weather avoidance strategies for terminal-area flights” (Applicant Remarks page 13).
The Examiner has considered the arguments presented and respectfully disagrees. First, assertions of improvement in a technological field must not be directed to an abstract idea (see MPEP 2106). In Berkheimer v. HP INC., 881 F. 3d 1360 (Fed. Cir. 2018), the federal circuit held that improvements are only considered “to the extent they are captured in the claims.” Berkheimer at 1369. As written, the claims merely describe the method for generating a flight strategy and do not outline improvements to the technological field. Therefore, the Applicant’s arguments are not persuasive.
Second, under the 35 U.S.C. 101 Analysis, the recited collecting and acquiring steps is mere data gathering for use in the determination and formulation steps and constitutes insignificant extra-solution activity which does not impose meaningful limits on the claim (MPEP 2106.05(g)).
For these reasons, the Examiner maintains the 35 U.S.C. 101 rejection.
35 U.S.C. 103
Applicant’s arguments, see Applicant Remarks, filed on January 30, 2026, with respect to the rejection(s) of claim(s) 1-10 and 20 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Chaubey et al. (U.S. Patent Publication Number 2022/0139234).
Allowable Subject Matter
Claims 4-5, 7-9, and 25 are rejected under 35 U.S.C. 101 and are dependent upon a rejected base claim. Additionally, claims 11-19 are rejected under 35 U.S.C. 112. However, claims 4-5, 7-9, and 25 would be allowable if rewritten to overcome the 35 U.S.C. 101 rejection and 35 U.S.C. 112 rejection (for claims 11-19, see the 35 U.S.C. 112 rejection above) and rewritten in independent form including all of the limitations of the base claim and any intervening claims. As allowable subject matter has been indicated, applicant's reply must either comply with all formal requirements or specifically traverse each requirement not complied with. See 37 CFR 1.111(b) and MPEP § 707.07(a).
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1
Claim 1. A method for generating a weather avoidance strategy for flights, the method comprising:
collecting, by a computing apparatus comprising a processor and a storage unit, historical radar trajectory data and historical weather data of various flights in a predetermined airport terminal area, and receiving, via a communication unit, weather forecast data in real time;
determining an arrival and departure typical flight route of each flight in the predetermined airport terminal area on a basis of the historical radar trajectory data and the historical weather data;
acquiring deviation information indicating deviation of each flight due to severe convective weather on the basis of the historical weather data, the arrival and departure typical flight route, and the historical radar trajectory data;
determining flight deviation probabilities under different weather conditions on the basis of the historical weather data, the arrival and departure typical flight route and the deviation information, to generate a flight deviation probability chart;
constructing a weather avoidance probability figure of the predetermined airport terminal area on the basis of the weather forecast data and the flight deviation probability chart;
formulating a weather avoidance strategy for each flight in the predetermined airport terminal area on the basis of the arrival and departure typical flight route and the weather avoidance probability figure; and
providing the weather avoidance strategy for each flight as a reference for controllers to plan arrival and departure flight routes of the flights in the predetermined airport terminal area under convective weather conditions.
101 Analysis - Step 1: Statutory category – Yes
The claim recites a method including at least one step. The claim falls within one of the four statutory categories. See MPEP 2106.03.
101 Analysis - Step 2A Prong one evaluation: Judicial Exception – Yes – Mental processes
In Step 2A, Prong one of the 2019 Patent Eligibility Guidance (PEG), a claim is to be analyzed to determine whether it recites subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) mental processes, and/or c) certain methods of organizing human activity.
The Office submits that the foregoing bolded limitation(s) constitutes judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the limitations can be “performed in the human mind, or by a human using a pen and paper”. See MPEP 2106.04(a)(2)(III)
The claim recites the limitation of determining an arrival and departure typical flight route of each flight in the predetermined airport terminal area on a basis of the historical radar trajectory data and the historical weather data; determining flight deviation probabilities under different weather conditions on the basis of the historical weather data, the arrival and departure typical flight route and the deviation information, to generate a flight deviation probability chart; constructing a weather avoidance probability figure of the predetermined airport terminal area on the basis of the weather forecast data and the flight deviation probability chart; and formulating a weather avoidance strategy for each flight in the predetermined airport terminal area on the basis of the arrival and departure typical flight route and the weather avoidance probability figure; and providing the weather avoidance strategy for each flight as a reference for controllers to plan arrival and departure flight routes of the flights in the predetermined airport terminal area under convective weather conditions.
This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is, nothing in the claim elements precludes the step from practically being performed in the mind. For example, the claim encompasses a person looking at data collected and forming a simple judgement. For example, the person would read the collected data and make a mental determination of the arrival and departures of flight routes according to historical records. The person would further determine the chance of a flight requiring deviation due to weather conditions based on historical weather data and the corresponding flight route. Based on the information and with the aid of pen and paper, the person would be able to construct a general probability of deviation based on a weather forecast and create a weather avoidance strategy to avoid the weather conditions. Further, the person may verbally or physically provide the strategy for each flight to be referenced in planning the arrival and departure flight routes.
Thus, the claim recites a mental process.
101 Analysis - Step 2A Prong two evaluation: Practical Application - No
In Step 2A, Prong two of the 2019 PEG, a claim is to be evaluated whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in MPEP 2106.04(d), 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, such that the claim is more than a drafting effort designed to monopolize the judicial exception. The courts have indicated that additional elements such as: merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
The Office submits that the foregoing underlined limitation(s) recite additional elements that do not integrate the recited judicial exception into a practical application.
The claim recites additional elements or steps of collecting historical radar trajectory data and historical weather data of various flights in a predetermined airport terminal area, and collecting weather forecast data in real time; acquiring deviation information indicating deviation of each flight due to severe convective weather on the basis of the historical weather data, the arrival and departure typical flight route, and the historical radar trajectory data.
The collecting and acquiring information steps are recited at a high level of generality (i.e. as a general means of gathering data for the determining steps), and amount to mere data gathering, which is a form of insignificant extra-solution activity.
Accordingly, even in combination, these additional steps do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
101 Analysis - Step 2B evaluation: Inventive concept - No
In Step 2B of the 2019 PEG, a claim is to be evaluated as to whether the claim, as a whole, amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the receiving steps and the displaying step were considered to be insignificant extra-solution activity in Step 2A, and thus they are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The background recites that the sensors are all conventional sensors mounted on the vehicle, and the specification does not provide any indication that the vehicle controller is anything other than a conventional computer within a vehicle. 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 (as it is here). Further, 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. Accordingly, a conclusion that the collecting step is well-understood, routine, conventional activity is supported under Berkheimer.
Thus, the claim is ineligible.
Dependent Claims
Dependent claims(s) 4-10 and 20-29 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of the 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. Therefore, dependent claims 4-10 and 12-20 are not patent eligible under the same rationale as provided for in the rejection of the independent claims.
Therefore, claims 1-10 and 20-29 are ineligible under 35 USC §101.
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.
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.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 6, 10, 20, 23, and 26-29 are rejected under 35 U.S.C. 103 as being unpatentable over Holder et al. (U.S. Patent Publication Number 2020/0168104) in view of Gu et al. (U.S. Patent Publication Number 2022/0076583).
Regarding claim 1, Holder discloses a method for generating a weather avoidance strategy for flights, the method comprising:
collecting historical radar trajectory data and historical weather data of various flights in a predetermined airport terminal area (Holder ¶ 69 discloses “The example routing patterns processor 236 is a machine learning system that merges historical air traffic data with weather data,” wherein merging data first requires to have collected the data; therefore, the processor collects historical air traffic and weather data. The processor uses machine learning to merge historical air traffic [control] data and weather data with current traffic and ATC routine. One having ordinary skill in the art would recognize that air traffic data from air traffic control (ATC) includes radar data, see Lincoln Laboratory “A global mode of tracking aircraft”), and collecting weather forecast data in real time; (Holder ¶ 70 “The example tracking processor is configured to continuously monitor weather data”)
determining an arrival and departure typical flight route of each flight in the predetermined airport terminal area on a basis of the historical radar trajectory data and the historical weather data; (Holder ¶ 34 discloses storing and providing, thereby having determined, air traffic control (ATC) data which includes “airport arrival rate, arrival/departure taxi time,” “current weather data” and “weather services”)
acquiring deviation information indicating deviation of each flight due to severe convective weather on the basis of the historical weather data, the arrival and departure typical flight route, and the historical radar trajectory data; (Holder ¶ 35 discloses “flight plan deviation assistant functionality that includes identifying deviation conditions (e.g., weather causing a flight plan deviation, airport closures, runway closures, special airspace, or the like)”)
Holder does not expressly disclose:
determining flight deviation probabilities under different weather conditions on the basis of the historical weather data, the arrival and departure typical flight route and the deviation information, to generate a flight deviation probability chart;
constructing a weather avoidance probability figure of the predetermined airport terminal area on the basis of the weather forecast data and the flight deviation probability chart; and
formulating a weather avoidance strategy for each flight in the predetermined airport terminal area on the basis of the arrival and departure typical flight route and the weather avoidance probability figure; and
providing the weather avoidance strategy for each flight as a reference for controllers to plan arrival and departure flight routes of the flights in the predetermined airport terminal area under convective weather conditions.
However, Gu discloses:
determining flight deviation probabilities under different weather conditions on the basis of the historical weather data, the arrival and departure typical flight route and the deviation information, to generate a flight deviation probability chart; (Gu ¶ 44 discloses outputting “a classification vector representing accurate probabilities that the flight interval includes at least one flight path deviation,” wherein the deviation is based on historical flight data, the flight data including weather patterns, see ¶ 46, such that the deviation includes a holding pattern to delay the aircraft from arriving as a result of poor weather, see ¶ 30, and wherein the probabilities are generated as a vector of values from an activation map, see ¶ 59, wherein a map is a chart, see Merriam-Webster, “chart”.)
constructing a weather avoidance probability figure of the predetermined airport terminal area on the basis of the weather forecast data and the flight deviation probability chart; and (Gu ¶ 65 discloses “generate a plurality of probabilities, with each of the probabilities indicating a likelihood that the flight interval includes a particular flight path deviation,” the probabilities are generated as a vector of values from an activation map, see ¶ 59, wherein a map is a chart, see Merriam-Webster, “chart”)
formulating a weather avoidance strategy for each flight in the predetermined airport terminal area on the basis of the arrival and departure typical flight route and the weather avoidance probability figure; and (Gu ¶ 52 discloses “if flight path deviations in a particular route tend to occur at a particular time, the flight optimization module 512 may suggest a modification of a flight schedule to avoid those times and thereby reduce the chances of flight path deviations,” wherein the flight path deviation occurs due to a weather condition, see ¶ 25, and the flight path is between a departure point 108 and a destination 110, see ¶ 30).
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the determining that a deviation condition exists, as disclosed by Holder, with determining flight deviation probabilities and constructing a weather avoidance probability figure, as disclosed by Gu, with reasonable expectation of success, to generate more accurate flight classifications (Gu ¶ 22), rendering the limitation to be an obvious modification.
Chaubey discloses:
providing the weather avoidance strategy for each flight as a reference for controllers to plan arrival and departure flight routes of the flights in the predetermined airport terminal area under convective weather conditions. (Chaubey ¶ 14 discloses determining “a recommended flight path from the current position of the aircraft for recapturing a previously-planned reference descent strategy,” the reference descent strategy for thereby having been provided, and “satisfying an upcoming constraint associated with the reference descent strategy,” wherein the operation of aircraft 102 is supported by “an air traffic management system, [i.e., controllers],” see ¶ 24, and wherein the upcoming constraint includes a “required time of arrival (RTA),” see ¶ 14.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the determining of an arrival and departure typical flight route of each flight in the predetermined airport terminal area of Holder with using a provided weather avoidance strategy for each flight as a reference, as disclosed by Chaubey, with reasonable expectation of success, because one having ordinary skill in the art would recognize that airports manage both the arrival and departure of flights in and out of the terminal, see “Algorithms for Control of Arrival and Departure Traffic in Terminal Airspace.”
Further, it would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the combination of Holder and Gu to incorporate providing the weather avoidance strategy for each flight as a reference for controllers to plan arrival and departure flight routes of the flights in the predetermined airport terminal area under convective weather conditions, as disclosed by Chaubey, with reasonable expectation of success, to autonomously return an aircraft to an optimal descent strategy, resulting in improved cost management and ensuring safety and compliance with applicable constraints (Chaubey ¶ 58), rendering the limitation to be an obvious modification.
Regarding claim 2, Holder in combination with Gu and Chaubey discloses the method according to Claim 1, wherein:
determining an arrival and departure typical flight route in the predetermined airport terminal area on the basis of the historical radar trajectory data and the historical weather data comprises: extracting the historical radar trajectory data of a plurality of flights in good weather conditions on the basis of the historical radar trajectory data and the historical weather data; and (Holder ¶ 34 discloses weather data aggregators and traffic data aggregators for server system 110, thereby extracting, weather data which includes wind speed, cloud cover, visibility, precipitation, temperature, and merging “historical air traffic data with weather data and current traffic and ATC routing to show what the ATC is currently doing and to predict changes when there is a significant event such as weather or airport closure,” see ¶ 69, wherein the weather condition is compared to a “normal checklist,” see ¶ 85, and continuously monitoring weather data “to provide a notice to the flight crew when the ceiling at the destination approaches minimums or may be below minimums,” see ¶ 121)
calculating the arrival and departure typical flight route in the predetermined airport terminal area on the basis of the extracted historical radar trajectory data of the plurality of flights. (Holder ¶ 30 discloses providing “deviation assistance capabilities that identify conditions requiring an aircraft to divert and provide candidate flight plan modifications from which a new flight plan may be selected or automatically generated [i.e., calculated].” Also see ¶ 62.)
Regarding claim 6, Holder in combination with Gu and Chaubey discloses the method according to Claim 1, wherein:
acquiring deviation information indicating deviation of each flight due to severe convective weather on the basis of the historical weather data, the arrival and departure typical flight route, and the historical radar trajectory data comprises: judging whether the arrival and departure typical flight route is in a severe convective weather condition on the basis of the historical weather data and the arrival and departure typical flight route; (Holder ¶ 58 discloses providing “official notifications and/or alerts based on external data and flight conditions (e.g., severe weather conditions ...”)
comparing the distance between the arrival and departure typical flight route determined to be in the severe convective weather condition and an actual radar trajectory of each flight based on the historical radar trajectory data with a predetermined deviation threshold; and (Gu ¶ 41 discloses a flight analysis module 412 that classifies a flight interval to include a deviation based on “if the actual flight route is determined to deviate from the planned flight route by more than the predetermined distance for at least a predetermined number of successive flight intervals,” wherein the weather causing the deviation includes “unexpectedly turbulent air [i.e., severe convective weather],” see ¶ 30)
acquiring, on the basis of the comparison result, deviation information indicating deviation of each flight due to the severe convective weather. (Gu ¶ 41 discloses identifying, thereby having acquired, the “flight path deviation based on a comparison between an actual flight route and a planned flight route within the flight interval,” wherein the weather causing the deviation includes “unexpectedly turbulent air [i.e., severe convective weather],” see ¶ 30)
Regarding claim 10, Holder in combination with Gu and Chaubey discloses the method according to Claim 1, wherein:
the historical radar trajectory data comprises at least one of: time, call sign, ground speed, altitude, and longitude and latitude. (Holder ¶ 69 discloses “historical air traffic data,” the air traffic control (ATC) data including “airport, runway length, ATIS, airport arrival rate, arrival/departure taxi time,” see ¶ 34. One having ordinary skill in the art would recognize that air traffic data from air traffic control (ATC) includes radar data, see “A global mode of tracking aircraft”).
Regarding claim 20, Holder in combination with Gu and Chaubey discloses the computer-readable program medium, storing a program which, when executed by a processor, implements the method according to Claim 1. (Holder in at least ¶ 47)
Regarding claim 21, Holder in combination with Gu and Chaubey discloses the method according to Claim 1, wherein determining the arrival and departure typical flight route comprises:
extracting historical radar trajectory data of flights occurring under weather conditions at or below a predefined convective weather level and determining the arrival and departure typical flight route based on the extracted historical radar trajectory data. (Holder ¶ 34 discloses weather data aggregators and traffic data aggregators for server system 110, thereby extracting, weather data which includes wind speed, cloud cover, visibility, precipitation, temperature, and merging “historical air traffic data with weather data and current traffic and ATC routing to show what the ATC is currently doing and to predict changes when there is a significant event such as weather or airport closure,” see ¶ 69, wherein the weather condition is compared to a “normal checklist,” see ¶ 85, and continuously monitoring weather data “to provide a notice to the flight crew when the ceiling at the destination approaches minimums or may be below minimums,” see ¶ 121)
Regarding claim 23, Holder in combination with Gu and Chaubey discloses the method according to Claim 1, wherein:
acquiring deviation information comprises determining whether a distance between an actual radar trajectory of a flight and the corresponding arrival and departure typical flight route exceeds a predetermined deviation threshold. (Gu ¶ 41 discloses a flight analysis module 412 that classifies a flight interval to include a deviation based on “if the actual flight route is determined to deviate from the planned flight route by more than the predetermined distance for at least a predetermined number of successive flight intervals,” wherein the weather causing the deviation includes “unexpectedly turbulent air [i.e., severe convective weather],” see ¶ 30, such that “the flight optimization module 512 may identify a plurality of likelihoods that each future flight may include a flight path deviation. In embodiments, if a likelihood associated with a particular future flight is above a certain threshold, the flight optimization module 512 may flag the future flight,” see ¶ 52, the deviations being measured by being “more than a predetermined distance for more than a predetermined period,” see ¶ 41)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the determining that a deviation condition exists, as disclosed by Holder, with determining whether a distance between an actual radar trajectory of a flight and the corresponding arrival and departure typical flight route exceeds a predetermined deviation threshold, as disclosed by Gu, with reasonable expectation of success, because such rule-based approaches generate accurate flight classification results and provide accurate and customizable results to facilitate detection of flight path deviation patterns among a plurality of flights (Gu ¶ 71), rendering the limitation to be an obvious modification.
Regarding claim 26, Holder in combination with Gu and Chaubey discloses the method according to Claim 1, wherein:
constructing the weather avoidance probability figure (Gu ¶ 44 outputting “a classification vector representing accurate probabilities that the flight interval includes at least one flight path deviation”) comprises dividing the predetermined airport terminal area into grids defined by longitude and latitude and assigning a deviation probability to each grid based on the weather forecast data and the flight deviation probability chart. (Gu ¶ 39 discloses “The image generation module 410 may map the plurality of coordinates into a two-dimensional coordinate space such that a representation of an actual route of the aircraft is depicted within the two-dimensional coordinate space [i.e., dividing the predetermined airport terminal area into grids defined by longitude and latitude],” and performing “flight path deviation classification,” wherein a deviation may be “at an airport of the destination,” see ¶ 25, and determining “whether the flight interval depicted in a particular one of the sub-flight images includes or does not include at least one flight path deviation [i.e., a deviation probability],” wherein each sub-flight is defined by a plurality of coordinates, see at least ¶ 55. One having ordinary skill in the art would recognize that coordinates of a map constitute a grid.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the determining that a deviation condition exists, as disclosed by Holder, with determining flight deviation probabilities and constructing a weather avoidance probability figure, as disclosed by Gu, with reasonable expectation of success, to generate more accurate flight classifications (Gu ¶ 22), rendering the limitation to be an obvious modification.
Regarding claim 27, Holder in combination with Gu and Chaubey discloses the method according to Claim 26, wherein:
the deviation probability assigned to each grid is classified into a no-need-of-deviation range, a possible-deviation range, or a necessary-deviation range to form the weather avoidance probability figure. (Gu ¶ 41 “the flight analysis module 412 may classify a flight interval as including or not including a flight deviation by comparing an actual direction of the aircraft during the flight to a planned direction,” wherein the classification is based on a map output that contains a probability vector that represents a probability that a flight interval “contains a particular flight path deviation or a portion of a flight path deviation,” see ¶ 59)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the determining that a deviation condition exists, as disclosed by Holder, with a deviation probability assigned to each grid being classified into a possible-deviation range to form the weather avoidance probability figure, as disclosed by Gu, with reasonable expectation of success, to provide comprehensive and accurate flight path deviation characterization, enabling flight path deviations to be identified and detected in a computationally efficient manner and further expand computational capabilities in the field of route pattern detection and flight optimization (Gu ¶ 24), rendering the limitation to be an obvious modification.
Regarding claim 28, Holder in combination with Gu and Chaubey discloses the method according to Claim 1, wherein:
formulating the weather avoidance strategy comprises determining whether grids classified as the necessary-deviation range cover at least a predetermined number of cross-sections of the arrival and departure typical flight route. (Gu ¶ 52 discloses generating [i.e., formulating] “recommended route changes [i.e., weather avoidance strategy]” such that “if a particular planned route is associated with numerous flights identified to include a flight path deviation such as a detour, the flight optimization module 512 may identify an alternative route between the same departure point and destination. One having ordinary skill in the art would recognize that numerous flights identified to include a flight path deviation is a cross section of the arrival and departure typical flight route, wherein “a predetermined number” may be at least one, under the broadest reasonable interpretation. Also see ¶ 55 disclosing that a “sub-flight image is of a segment of the flight path that overlaps with adjacent segments of the flight path”)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the weather avoidance strategy of Holder with determining whether grids classified as the necessary-deviation range cover at least a predetermined number of cross-sections of the arrival and departure typical flight route, as disclosed by Gu, with reasonable expectation of success because by overlapping the sub-flight images, the flight analysis module may characterize any flight path deviations contained in the flight data more accurately (Gu ¶ 55), rendering the limitation to be an obvious modification.
Regarding claim 29, Holder in combination with Gu and Chaubey discloses the method according to Claim 1, wherein:
formulating the weather avoidance strategy comprises selecting at least one of an airborne holding strategy, a ground waiting strategy, a no-impact strategy, an intrusion strategy, a diversion strategy, an arrival or departure point change strategy, an initial approach fix change strategy, or a radar guidance strategy based on the weather avoidance probability figure. (Holder ¶ 43 discloses that “Data received by the communication device 208 may include, without limitation: weather data, airport data, runway data, air traffic control (ATC) data, airport arrival delays, airport departure delays, “hold” notifications and/or holding patterns associated with particular waypoints,” wherein a “required holding pattern” at a particular waypoint may be “based on external data and flight conditions” such as “sever weather conditions,” see ¶ 58.)
Claims 3 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Holder et al. (U.S. Patent Publication Number 2020/0168104) in view of Gu et al. (U.S. Patent Publication Number 2022/0076583), further in view of Bombelli (“Strategic Air Traffic Planning with Fréchet Distance Aggregation and Rerouting”).
Regarding claim 3, Holder in combination with Gu and Chaubey does not expressly disclose the method according to Claim 2, wherein:
calculating the arrival and departure typical flight route in the predetermined airport terminal area on the basis of the extracted historical radar trajectory data of the plurality of flights comprises: estimating a distance between historical radar trajectories of any two flights among the plurality of flights by using Frechet distance, to construct a distance matrix; and clustering the constructed distance matrix using a clustering algorithm, to calculate the arrival and departure typical flight route.
However, Bombelli discloses:
calculating the arrival and departure typical flight route in the predetermined airport terminal area on the basis of the extracted historical radar trajectory data of the plurality of flights comprises: estimating a distance between historical radar trajectories of any two flights among the plurality of flights by using Frechet distance, to construct a distance matrix; and (Bombelli Introduction discloses using the Frechet distance as a measure for aggregating trajectories, wherein the Frechet distance is calculated [i.e., estimated], see Section B, which includes grouping trajectories [i.e., any two flights] that are spatially similar, see section B, wherein the Frechet distance is characterized in a matrix, see section C.)
clustering the constructed distance matrix using a clustering algorithm, to calculate the arrival and departure typical flight route. (Bombelli Section B discloses clustering together relevant trajectories based on spatial similarities using the Frechet distance.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the combination of Holder and Gu to incorporate using a Frechet distance to perform clustering of the routes, as disclosed by Bombelli, with reasonable expectation of success, to quantify and minimize issues when aggregating routes and to maintain compact and intuitive clusters (Bombelli Section B), rendering the limitation to be an obvious modification.
Regarding claim 22, Holder in combination with Gu and Chaubey does not expressly disclose the method according to Claim 21, wherein:
determining the arrival and departure typical flight route comprises estimating distances between historical radar trajectories of flights using Frechet distance and clustering the estimated distances to obtain the arrival and departure typical flight route.
However, Bombelli discloses:
determining the arrival and departure typical flight route comprises estimating distances between historical radar trajectories of flights using Frechet distance and clustering the estimated distances to obtain the arrival and departure typical flight route. (Bombelli Introduction discloses using the Frechet distance as a measure for aggregating trajectories, wherein the Frechet distance is calculated [i.e., estimated], see Section B, which includes grouping trajectories [i.e., any two flights] that are spatially similar, see section B, wherein the Frechet distance is characterized in a matrix, see section C.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the combination of Holder and Gu to incorporate using a Frechet distance to perform clustering of the routes, as disclosed by Bombelli, with reasonable expectation of success, to quantify and minimize issues when aggregating routes and to maintain compact and intuitive clusters (Bombelli Section B), rendering the limitation to be an obvious modification.
Claim 24 is rejected under 35 U.S.C. 103 as being unpatentable over Holder et al. (U.S. Patent Publication Number 2020/0168104) in view of Gu et al. (U.S. Patent Publication Number 2022/0076583) and Chaubey et al. (U.S. Patent Publication Number 2022/0139234), further in view of Pang et al. (“Aircraft Trajectory Prediction using LSTM Neural Network with Embedded Convolutional Layer”).
Regarding claim 24, Holder in combination with Gu and Chaubey does not expressly disclose the method according to Claim 1, wherein:
determining the flight deviation probabilities comprises calculating a predetermined percentile of vertically integrated liquid water content and a predetermined percentile of echo top along the arrival and departure typical flight route of each flight.
However, Pang discloses:
determining the flight deviation probabilities comprises calculating a predetermined percentile of vertically integrated liquid water content and a predetermined percentile of echo top along the arrival and departure typical flight route of each flight. (Pang Section 3 discloses that aircrafts tend to frequently deviate from the last on-file flight, wherein storm severity are indicated by vertically integrated liquid (VIL) and echo top (ET), see Section 2.2, and wherein the aircraft trajectory may be adjusted under convective weather influence, see Section 2.2.)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the determining that a deviation condition exists, as disclosed by Holder, of the combination of Holder, Gu, and Chauvey, with determining the flight deviation probabilities comprises calculating a predetermined percentile of vertically integrated liquid water content and a predetermined percentile of echo top along the arrival and departure typical flight route of each flight, as disclosed by Pang, with reasonable expectation of success, to reduce the weather-related safety uncertainties (Pang Section 5), and because convective weather conditions can develop rapidly and pose danger to mid-air traffic activities among the United States airspace (Pang Section 1) rendering the limitation to be an obvious modification.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/STEPHANIE T SU/Patent Examiner, Art Unit 3662