DETAILED ACTION
This Office Action is taken in response to Applicant’s Amendment and Remarks filed on 01/05/2026 regarding Application No. 17/896,368 originally filed on 08/26/2022. Claims 1-2 and 4-21 as filed are currently pending and have been considered as follows:
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 .
Response to Arguments
The applicant argues that the amended limitation requiring “processing flight planning simulations using the integrated flight data generated from the flight data and the subregion data to generate the airspace design” is not taught or suggested by Evans because Evans allegedly relies on parameter-driven voxel scoring rather than an integrated dataset formed from subregion and regional flight data prior to simulation [Remarks, pp. 7–8]. The examiner respectfully disagrees.
Parker expressly discloses integrating multiple sources of flight data and airspace data through a fusion process to generate a representation for modeling the airspace (as per “a fusion process 328 may be performed to combine and/or fuse multiple position updates/reports” in ¶166; ingestion of airspace data and flight data for modeling in ¶126). Evans discloses processing flight planning simulations by analyzing travel through sequences of airspace voxels and generating flight plans based on that analysis (¶56, ¶58). The rejection does not rely on Evans alone for the integration step; rather, Parker provides the integrated flight data generated from regional and subregion sources, and Evans provides the simulation-based processing of flight plans using such data. Combining Parker’s integrated airspace modeling framework with Evans’ simulation and flight plan generation would have been an obvious application of known techniques to an already integrated airspace dataset. Accordingly, applicant’s argument is unpersuasive.
The applicant further argues that Evans does not disclose “generating flight plans from flight planning simulations” processed using integrated flight data created by combining subregion data with regional flight data [Remarks, p. 9]. The examiner respectfully disagrees.
As discussed above, Parker discloses integrating airspace and flight data into a unified model for airspace management (¶117, ¶126, ¶166). Evans discloses generating recommended flight plans based on analysis of airspace voxels and flight parameters (¶15, ¶56, ¶74), including routes with departure and arrival locations (¶50). When Parker’s integrated dataset is used as the input to Evans’ simulation and route analysis engine, the resulting flight plans necessarily originate from simulations dependent on integrated flight data. The law does not require that a single reference explicitly disclose the entire pipeline; it is sufficient that the combined teachings would have rendered the claimed sequence obvious. Accordingly, applicant’s argument is unpersuasive.
The applicant argues that the limitation “validating, by the monitoring node, the integrated flight data by comparing the airspace design to a previous airspace design” is not taught or suggested by the cited art. Applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
The applicant argues that the prior art fails to teach or suggest “ranking the flight plans according to emissions output,” particularly where the plans are generated from simulations using integrated flight data [Remarks, pp. 9–10]. The examiner respectfully disagrees.
Kaivanto expressly discloses ranking flight options based on greenhouse-gas emissions and presenting relative emissions rankings to inform flight choice (Abstract). Evans discloses generating and scoring multiple flight plans based on various factors (¶57, ¶75). The combination of Parker, Evans, and Kaivanto renders obvious ranking the generated flight plans according to emissions output. Applying Kaivanto’s to the set of simulated flight plans generated by the combined Parker/Evans system would have been a predictable use of prior art elements according to their established functions. The fact that Kaivanto discusses consumer-facing rankings does not negate its teaching of emissions-based ordering of flight options. Therefore, applicant’s argument is unpersuasive.
The applicant argues that Evans does not disclose transmitting “flight plans ranked according to the emissions output” to an air navigation service provider after generation from simulations using integrated data [Remarks, p. 10]. The examiner respectfully disagrees.
Evans discloses outputting recommended flight plans to an external device or system (¶71, ¶76), including transmission of recommendations regarding potential flight plans. As discussed above, Kaivanto discloses ranking flight options based on emissions. Once the flight plans generated by Parker/Evans are ranked according to emissions in view of Kaivanto, transmitting those ranked plans to an external entity (such as an ANSP) constitutes the predictable use of Evans’ disclosed output and communication mechanisms. The combination of known generation, ranking, and transmission techniques would have yielded the claimed end-to-end process. The references need not expressly describe the exact phrasing “ranked by emissions deliverable sent to an ANSP” so long as the combined teachings render the claimed subject matter obvious. Accordingly, applicant’s argument is unpersuasive.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2, 4-8, 11, 19-21 are rejected under 35 U.S.C. 103 as being unpatentable over Parker (WO Pub. No. 2022064166) in view of Evans (US Pub. No. 20190103031) in view of Kaivanto (NPL Title: Rank-order concordance among conflicting emissions estimates for informing flight choice, Year: 2017) in further view of Sidiropoulos (US Pub. No. 20200143691).
As per Claim 1, Parker discloses a flight management system (as per Abstract), comprising:
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evaluating an airspace design of a subregion of a larger geographic region with the subregion being smaller than and contained within a geographic region airspace, (as per Fig. 1A)
receiving at a monitoring node subregion data for airspace of the subregion provider (as per “Airspace data, airspace condition data and/or non-flight data may comprise or represent data representative of the airspace environment and/or changes thereof of an airspace 1020, airspace region 1020a, airspace zone(s) 1080a-1080n and the like” in ¶75, as per Fig. 1B) the subregion data being received from an air navigation service that collects the subregion data , (as per “airspace definitions from airspace/aeronautical information provider(s) (AlPs); … Airspace data, airspace condition data and/or non-flight data may be generated and/or provided by one or more data services or airspace data sources that the flight management system 1000 may connect to over a communication network 1050.” in ¶75) and with the subregion data comprising airport, obstacle, and operational data about the subregion; (as per “AMC of the set of AMCs 526a uses the airspace model to detect any conflicts between, without limitation, for example aircraft within the corresponding airspace zone and/or other airspace infrastructure (e.g. weather systems, airports, restricted airspace and the like) within the airspace zone covered by the AMC.” in ¶191)
integrating the subregion data with flight data to generate integrated flight data that has been collected for the geographic region airspace with the flight data being maintained by the monitoring node (as per “Given that an entity may receive multiple flight data from multiple flight data sources 321 a, 321 b, 321 c each having a position update/report, a fusion process 328 may be performed to combine and/or fuse multiple position updates/reports.” in ¶166, as per “the AMCs of the multiple adjacent airspace zones may be deallocated and the airspace zones merged into a single airspace zone hosted by a corresponding AMC.” in ¶125, as per FIG. 1B) and the flight data comprising airport, obstacles, and operational data about the geographic region; (as per “AMC of the set of AMCs 526a uses the airspace model to detect any conflicts between, without limitation, for example aircraft within the corresponding airspace zone and/or other airspace infrastructure (e.g. weather systems, airports, restricted airspace and the like) within the airspace zone covered by the AMC.” in ¶191)
integrated flight data generated from the flight data and the subregion data to generate the airspace design; (as per “identifying portions of the received flight data associated with each of one or more aircraft of the plurality of aircraft; combining the identified portions of received flight data for said each aircraft into a flight data message including data representative of a single canonical representation of flight data associated with an entity corresponding to said each aircraft; and sending each flight data message to the corresponding AMC for modelling the corresponding airspace zone stat” in ¶117, as per “, geospatial information that may be added to the flight data indicating which airspace zone the in-flight aircraft is traversing. Flight data may be received over a communication network from numerous flight data information sources 205a-205n, each of which may distribute flight data associated with aircraft to each of the corresponding FOCs 204a-204n. Furthermore airspace data/airspace condition data and/or non-flight data associated with the airspace environment… may be ingested from corresponding airspace information/data source(s) 213a-213n and/or flight database 212b/flight services 212 by each of the corresponding set of AMCs 210a-210f connected to the corresponding FOCs 204a-204n and/or flight database 212b of the flight services 212 and the like” in ¶126)
integrated flight data generated from the flight data and the subregion data, (as per “identifying portions of the received flight data associated with each of one or more aircraft of the plurality of aircraft; combining the identified portions of received flight data for said each aircraft into a flight data message including data representative of a single canonical representation of flight data associated with an entity corresponding to said each aircraft; and sending each flight data message to the corresponding AMC for modelling the corresponding airspace zone stat” in ¶117, as per “, geospatial information that may be added to the flight data indicating which airspace zone the in-flight aircraft is traversing. Flight data may be received over a communication network from numerous flight data information sources 205a-205n, each of which may distribute flight data associated with aircraft to each of the corresponding FOCs 204a-204n. Furthermore airspace data/airspace condition data and/or non-flight data associated with the airspace environment… may be ingested from corresponding airspace information/data source(s) 213a-213n and/or flight database 212b/flight services 212 by each of the corresponding set of AMCs 210a-210f connected to the corresponding FOCs 204a-204n and/or flight database 212b of the flight services 212 and the like” in ¶126)
Parker fails to expressly disclose:
processing flight planning simulations using the flight data
validating, by the monitoring node, the integrated flight data by comparing the airspace design to a previous airspace design;
generating flight plans from the flight planning simulations processed using the flight data with the flight plans covering the geographic region airspace and comprising planned routes through the airspace of the geographic region including entry points into and exit points out of the geographic region airspace to enable aircraft to fly through the geographic region airspace; and
ranking the flight plans according to emissions output;
transmitting the flight plans ranked according to the emissions output to the air navigation service provider.
Evans discloses of flight plan recommendation based on analysis of airspace voxels (as per Abstract), comprising:
processing flight planning simulations using the flight data (as per “UAV management device 260 can analyze a large quantity of flight plans, taking into account travel through different sequences of voxels from departure location to arrival location” in ¶56, as per “can combine voxels along a flight path from a departure location to an arrival location (e.g., a summation of all voxels, an average voxel score, a maximum voxel score, etc.) to calculate an overall score for the flight path. In some implementations, if a score is between thresholds, UAV management device 260 can output the score and/or factors that contributed to the score, and can request operator input as to whether to accept the flight plan” in ¶58)
generating flight plans from the flight planning simulations processed using the flight data with the flight plans covering the geographic region airspace (as per “the UAV management device can generate a recommendation based on the analysis described above. The recommendation can include, for example, a recommended flight plan for a UAV (as shown), a rejection of a proposed flight plan, an approval of a proposed flight plan, or the like” in ¶15, as per “can include a recommended flight plan. In this case, UAV management device 260 can determine the flight plan based on a best overall score for the flight plan, and/or based on individual scores (e.g., a risk score, a cost score, a time score, a network score, etc.) for the flight plan (e.g., based on combining scores for voxels included in the flight plan)” in ¶74)
comprising planned routes through the airspace of the geographic region including entry points into and exit points out of the geographic region airspace to enable aircraft to fly through the geographic region airspace; (as per “In some implementations, a flight plan can include a departure location (e.g., ground beneath a first voxel), an arrival location (e.g., ground beneath a second voxel), and/or multiple departure locations and arrival locations (for multiple deliveries of packages, for example). “ in ¶50)
transmitting the flight plans to the air navigation service provider. (as per “process 400 can include outputting a recommendation regarding the potential flight plan based on analyzing the one or more flight parameters and the plurality of airspace parameters (block 450).” in ¶71, as per “For example, UAV management device 260 can output a recommendation (e.g., to client device 280 via external network 250) regarding the potential flight plan based on analyzing the one or more flight parameters and the plurality of airspace parameters.” in ¶71)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Evans is concerned with airspace design.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the flight management system of Parker with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
Parker and Evans fail to expressly disclose:
validating, by the monitoring node, the integrated flight data by comparing the airspace design to a previous airspace design;
ranking the flight plans according to emissions output;
Kaivanto discloses of a rank-order concordance among conflicting emissions estimates for informing flight choice, comprising:
ranking the flight plans according to emissions output; (as per “When external considerations rule out alternative travel-modes, the relative ranking of flight options’ GHG emissions is sufficient to inform consumers’ decision making” in Abstract, as per “A credible and ambiguity-free alternative would thus be to display GHG ranking information on the front page of flight search-engine results” in Abstract)
In this way, Kaivanto operates to rank flight options by their greenhouse‑gas footprint (Abstract). Like Parker and Evans, Kaivanto is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker and Evans with the teachings of Kaivanto to enable another standard means of ranking flight plans (Abstract).
Parker, Evans, and Kaivanto fail to expressly disclose:
validating, by the monitoring node, the integrated flight data by comparing the airspace design to a previous airspace design;
Sidiropoulos discloses of airspace information modeling and design, comprising:
validating, by the monitoring node, (as per “at operation 1030, performing a validation of the airspace design against a first aviation standard, the validation comprising a set of design rules and criteria for evaluation of aircraft performance and safety of operations” in ¶269) the integrated flight data by comparing the airspace design to a previous airspace design; (as per “effective communication of proposed improvement plans to the public, offering visual “as-is” to “proposed” scenario comparisons with complete environmental impact evaluation and noise exposure assessment in particular” in ¶45, as per “Once the user has concluded a design, they are able to save all its parameters and assign a designation to it. AIM enables comparison of multiple scenarios side-by-side, whereas a relevant view snapshot (e.g., map control and vertical profile control for the case of route comparison) from both scenarios are displayed side-by-side” in ¶261, as per “5. Assessment of proposed design scenarios and capability for comparison” in ¶41)
In this way, Sidiropoulos operates to rank flight options by their greenhouse‑gas footprint (Abstract). Like Parker, Evans, and Kaivanto, Sidiropoulos is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Evans, and Kaivanto with the scenario comparison and validation teachings of Sidiropoulos to validate the integrated flight data by comparing the generated airspace design to a previously stored airspace design, as Sidiropoulos expressly discloses saving airspace designs and enabling "as-is to proposed scenario comparisons" (¶45) as well as side-by-side comparison of saved design scenarios (¶260-¶261) for validation and evaluation purposes. Such a modification would have been an obvious application of known airspace design validation techniques to ensure that newly integrated flight data produces a coherent airspace design consistent with prior design states.
As per Claim 2, the combination Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker further discloses receiving the subregion data in Aeronautical Information Exchange Model (AIXM) format. (“The one or more other flight data information sources may further include, without limitation, for example at least one from the group of: another aircraft; a radar detecting position of said aircraft; All Purpose Structured Eurocontrol Surveillance Information Exchange (ASTERIX) air traffic services information; airspace surveillance data associated with one or more of said plurality of aircraft; automatic dependent surveillance broadcast, ADS-B, data associated with one or more of said aircraft; flight planning services configured for providing flight plans of one or more of the aircraft of the plurality of aircraft; any other standard for exchange of air traffic services information and the like.” in ¶94)
As per Claim 4, the combination Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker fails to expressly disclose generating the flight plans for flights within Free Route Airspace (FRA) that extend within the airspace of the subregion.
See Claim 1 for teachings of Evans. Evans further discloses generating the flight plans for flights within Free Route Airspace (FRA) that extend within the airspace of the subregion. (as per “the recommended flight plan can provide information to instruct and/or control the UAV to depart from voxel B, and then to proceed to voxel D rather than voxel A because voxel A has a high occupancy. Continuing with the example, the recommended flight plan can provide information to instruct and/or control the UAV to avoid voxel F (e.g., to prevent violation of a noise ordinance associated with voxel F), and to proceed from voxel D to voxel C to voxel E to voxel G to the arrival location at voxel H.” in ¶16, as per “UAV management device can analyze a large quantity (e.g., hundreds, thousands, millions, etc.) of data points for a large quantity of UAVs to generate recommended flight plans for one or more UAVs” in ¶17)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Kaivanto, and Sidiropoulos, Evans is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Kaivanto, and Sidiropoulos with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
As per Claim 5, the combination Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker fails to expressly disclose processing the flight planning simulations using global weather data.
See Claim 1 for teachings of Evans. Evans further discloses processing the flight planning simulations using global weather data. (as per “an airspace parameter can represent one or more conditions that include one or more environmental conditions. For example, an environmental condition can include weather in an airspace voxel (e.g., wind, rain, snow, sleet, hail, fog, clouds, sun, temperature, humidity, barometric pressure, etc.).” in ¶46)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Kaivanto, and Sidiropoulos, Evans is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Kaivanto, and Sidiropoulos with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
As per Claim 6, the combination Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker fails to expressly disclose processing the flight planning simulations using flight schedules for one or more of the geographic regions and the subregion.
See Claim 1 for teachings of Evans. Evans further discloses processing the flight planning simulations using flight schedules for one or more of the geographic regions and the subregion. (as per “process 400 can include receiving information that identifies an airspace voxel that represents a three-dimensional portion of airspace during a particular time period (block 410).” in ¶38, as per “UAV management device 260 can analyze a large quantity of flight plans, taking into account travel through different sequences of voxels from departure location to arrival location.” in ¶56)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Kaivanto, and Sidiropoulos, Evans is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Kaivanto, and Sidiropoulos with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
As per Claim 7, the combination Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker further discloses integrating the subregion data with the flight data comprises replacing a portion of the flight data with the subregion data. (“the fuse process 328 of the AMC 110a or 210a is configured to fuse this flight data or airspace data information together or select the most reliable flight data or airspace data information that the corresponding entity can use.” in ¶166, as per “flight data/airspace data from the flight information database 212b, as per “flight/airspace data source(s) 205a/213a, and/or telemetry from aircraft 206, may be used to update each of the airspace states modelled by each AMC 210a-210f.” in ¶130)
As per Claim 8, the combination Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker further discloses of generating the flight data of the geographic region airspace prior to receiving the subregion data from the air navigation service provider. (as per “airspace modelling component is configured to queue received flight data/airspace data messages associated with aircraft in flight in the airspace zone, and process the airspace zone state in a plurality of processing intervals, where each processing interval is configured to: update the modelled airspace zone state, prior to analyzing the modelled airspace zone state” in Claim 10, as per “The airspace model component of each AMC 110a of the set of AMCs 110a-110I is configured to generate, maintain and update an airspace model 118a corresponding to the air traffic 106a-106c within the airspace zone 108a based on the flight data stream 117a of received flight data corresponding to each aircraft 106a-106c transiting the airspace zone 108a” in ¶98)
As per Claim 11, the combination Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker fails to expressly disclose wherein ranking the flight plans is further based on one or more aspects comprising flight efficiencies and fuel usage.
See Claim 1 for teachings of Evans. Evans further discloses wherein ranking the flight plans is further based on one or more aspects comprising flight efficiencies and fuel usage. (as per “UAV management device 260 can generate scores for flight plans that take into account one or more of a risk factor (e.g., potential for collision or accident), a cost factor (e.g., energy consumption), a time factor (e.g., time of travel), a network factor (e.g., a risk, cost, or time factor to a network operator with infrastructure that support flight operations), and/or the like.” in ¶57, as per “the recommendation can include multiple flight plans with an option to select one (e.g., least risky vs. least costly vs. shortest flight time vs. least cost to the network, or some combination thereof, or top 3 scores with risk score, cost score, time score, network score, etc.)” in ¶75)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Kaivanto, and Sidiropoulos, Evans is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Kaivanto, and Sidiropoulos with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
As per Claim 19, Parker discloses a flight management system (as per Abstract), comprising:
non-transitory computer readable medium comprising instructions stored thereon that, when executed by processing circuitry of a computing device (as per ¶47)
maintain flight data for airspace of a geographic region (as per FIG. 1B), the flight data being devoid of data for a subregion that is contained within the geographic region; (as per “the AMCs of the multiple adjacent airspace zones may be deallocated and the airspace zones merged into a single airspace zone hosted by a corresponding AMC.” in ¶125, as per “incoming flight data and/or airspace data and the like that is being received from the flight data source(s) may be queued/buffered.” in ¶112)
receive subregion data for airspace of the subregion, the subregion data being received from an air navigation service provider; (as per “The flight orchestration layer includes a plurality of FOCs 204a - 204n, each of the FOCs 204a -204n covering a different one of the airspace regions 202a -202n.” in ¶124, as per “airspace data, airspace condition data and/or non-flight data may comprise or represent data representative of the airspace environment and/or changes thereof of an airspace 1020, airspace region 1020a, airspace zone(s) 1080a-1080n and the like such as, without limitation, for example airspace definitions from airspace/aeronautical information provider(s) (AlPs)” in ¶75)
integrate the subregion data with the flight data of the geographic region to generate integrated flight data; (as per “Given that an entity may receive multiple flight data from multiple flight data sources 321 a, 321 b, 321 c each having a position update/report, a fusion process 328 may be performed to combine and/or fuse multiple position updates/reports.” in ¶166, as per “the fuse process 328 of the AMC 110a or 210a is configured to fuse this flight data or airspace data information together or select the most reliable flight data or airspace data information that the corresponding entity can use.” in ¶166, as per “the AMCs of the multiple adjacent airspace zones may be deallocated and the airspace zones merged into a single airspace zone hosted by a corresponding AMC.” in ¶125, as per FIG. 1B)
integrated flight data generated from the flight data and the subregion data to generate an airspace design; (as per “identifying portions of the received flight data associated with each of one or more aircraft of the plurality of aircraft; combining the identified portions of received flight data for said each aircraft into a flight data message including data representative of a single canonical representation of flight data associated with an entity corresponding to said each aircraft; and sending each flight data message to the corresponding AMC for modelling the corresponding airspace zone stat” in ¶117, as per “, geospatial information that may be added to the flight data indicating which airspace zone the in-flight aircraft is traversing. Flight data may be received over a communication network from numerous flight data information sources 205a-205n, each of which may distribute flight data associated with aircraft to each of the corresponding FOCs 204a-204n. Furthermore airspace data/airspace condition data and/or non-flight data associated with the airspace environment… may be ingested from corresponding airspace information/data source(s) 213a-213n and/or flight database 212b/flight services 212 by each of the corresponding set of AMCs 210a-210f connected to the corresponding FOCs 204a-204n and/or flight database 212b of the flight services 212 and the like” in ¶126)
integrated flight data generated from the flight data and the subregion data, (as per “identifying portions of the received flight data associated with each of one or more aircraft of the plurality of aircraft; combining the identified portions of received flight data for said each aircraft into a flight data message including data representative of a single canonical representation of flight data associated with an entity corresponding to said each aircraft; and sending each flight data message to the corresponding AMC for modelling the corresponding airspace zone stat” in ¶117, as per “, geospatial information that may be added to the flight data indicating which airspace zone the in-flight aircraft is traversing. Flight data may be received over a communication network from numerous flight data information sources 205a-205n, each of which may distribute flight data associated with aircraft to each of the corresponding FOCs 204a-204n. Furthermore airspace data/airspace condition data and/or non-flight data associated with the airspace environment… may be ingested from corresponding airspace information/data source(s) 213a-213n and/or flight database 212b/flight services 212 by each of the corresponding set of AMCs 210a-210f connected to the corresponding FOCs 204a-204n and/or flight database 212b of the flight services 212 and the like” in ¶126)
Parker fails to expressly disclose:
process flight planning simulations using the flight data
validate the integrated flight data by comparing the airspace design to a previous airspace design;
generate flight plans from the flight planning simulations processed using flight data with the flight plans comprising entry points and exit points for the geographic region; and
ranking the flight plans according to emissions output;
transmitting the flight plans ranked according to the emissions output to the air navigation service provider.
Evans discloses of flight plan recommendation based on analysis of airspace voxels (as per Abstract), comprising:
process flight planning simulations using the flight data (as per “UAV management device 260 can analyze a large quantity of flight plans, taking into account travel through different sequences of voxels from departure location to arrival location” in ¶56, as per “can combine voxels along a flight path from a departure location to an arrival location (e.g., a summation of all voxels, an average voxel score, a maximum voxel score, etc.) to calculate an overall score for the flight path. In some implementations, if a score is between thresholds, UAV management device 260 can output the score and/or factors that contributed to the score, and can request operator input as to whether to accept the flight plan” in ¶58)
generate flight plans from the flight planning simulations processed using flight data (as per “the UAV management device can generate a recommendation based on the analysis described above. The recommendation can include, for example, a recommended flight plan for a UAV (as shown), a rejection of a proposed flight plan, an approval of a proposed flight plan, or the like” in ¶15, as per “can include a recommended flight plan. In this case, UAV management device 260 can determine the flight plan based on a best overall score for the flight plan, and/or based on individual scores (e.g., a risk score, a cost score, a time score, a network score, etc.) for the flight plan (e.g., based on combining scores for voxels included in the flight plan)” in ¶74)
with the flight plans comprising entry points and exit points for the geographic region; and (as per “In some implementations, a flight plan can include a departure location (e.g., ground beneath a first voxel), an arrival location (e.g., ground beneath a second voxel), and/or multiple departure locations and arrival locations (for multiple deliveries of packages, for example). “ in ¶50)
transmit the flight plans to the air navigation service provider. (as per “process 400 can include outputting a recommendation regarding the potential flight plan based on analyzing the one or more flight parameters and the plurality of airspace parameters (block 450).” in ¶71, as per “For example, UAV management device 260 can output a recommendation (e.g., to client device 280 via external network 250) regarding the potential flight plan based on analyzing the one or more flight parameters and the plurality of airspace parameters.” in ¶71)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Evans is concerned with airspace design.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the flight management system of Parker with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
Parker and Evans fail to expressly disclose:
validate the integrated flight data by comparing the airspace design to a previous airspace design;
ranking the flight plans according to emissions output;
Kaivanto discloses of a rank-order concordance among conflicting emissions estimates for informing flight choice, comprising:
ranking the flight plans according to emissions output; (as per “When external considerations rule out alternative travel-modes, the relative ranking of flight options’ GHG emissions is sufficient to inform consumers’ decision making” in Abstract, as per “A credible and ambiguity-free alternative would thus be to display GHG ranking information on the front page of flight search-engine results” in Abstract)
In this way, Kaivanto operates to rank flight options by their greenhouse‑gas footprint (Abstract). Like Parker and Evans, Kaivanto is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker and Evans with the teachings of Kaivanto to enable another standard means of ranking flight plans (Abstract).
validate the integrated flight data by comparing the airspace design to a previous airspace design;
Sidiropoulos discloses of airspace information modeling and design, comprising:
validate the integrated flight data (as per “at operation 1030, performing a validation of the airspace design against a first aviation standard, the validation comprising a set of design rules and criteria for evaluation of aircraft performance and safety of operations” in ¶269) by comparing the airspace design to a previous airspace design;(as per “effective communication of proposed improvement plans to the public, offering visual “as-is” to “proposed” scenario comparisons with complete environmental impact evaluation and noise exposure assessment in particular” in ¶45, as per “Once the user has concluded a design, they are able to save all its parameters and assign a designation to it. AIM enables comparison of multiple scenarios side-by-side, whereas a relevant view snapshot (e.g., map control and vertical profile control for the case of route comparison) from both scenarios are displayed side-by-side” in ¶261, as per “5. Assessment of proposed design scenarios and capability for comparison” in ¶41)
In this way, Sidiropoulos operates to rank flight options by their greenhouse‑gas footprint (Abstract). Like Parker, Evans, and Kaivanto, Sidiropoulos is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Evans, and Kaivanto with the scenario comparison and validation teachings of Sidiropoulos to validate the integrated flight data by comparing the generated airspace design to a previously stored airspace design, as Sidiropoulos expressly discloses saving airspace designs and enabling "as-is to proposed scenario comparisons" (¶45) as well as side-by-side comparison of saved design scenarios (¶260-¶261) for validation and evaluation purposes. Such a modification would have been an obvious application of known airspace design validation techniques to ensure that newly integrated flight data produces a coherent airspace design consistent with prior design states.
As per Claim 20, the combination Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 19. Parker fails to expressly discloses flight plans extending through the airspace over the subregion.
See Claim 19 for teachings of Evans. Evans further discloses flight plans extending through the airspace over the subregion. (as per “the recommendation can include a recommended flight plan from the departure location (at voxel B) to the arrival location (at voxel H). In this case, the recommended flight plan can provide information to instruct and/or control the UAV to depart from voxel B, and then to proceed to voxel D rather than voxel A because voxel A has a high occupancy. Continuing with the example, the recommended flight plan can provide information to instruct and/or control the UAV to avoid voxel F (e.g., to prevent violation of a noise ordinance associated with voxel F), and to proceed from voxel D to voxel C to voxel E to voxel G to the arrival location at voxel H.” in ¶16, as per ¶17)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Kaivanto, and Sidiropoulos, Evans is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Kaivanto, and Sidiropoulos with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
As per Claim 21, the combination Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker further discloses wherein integrating the subregion data with the flight data comprises supplementing the flight data (as per “The airspace model component of each AMC 110a is also configured to receive airspace data and/or airspace condition data associated with each of the airspace zones 108a-108e from one or more data services and/or airspace data sources for use in modelling and generating the airspace state of said each airspace zones” in ¶99) with the subregion data. (as per “the received airspace data and/or airspace condition data associated with a particular airspace zone 108a of the airspace zones 108a-108e in the airspace region 102a covered by AMC 110a is used by the corresponding airspace modelling component of the AMC 110a for modelling static objects/entities or non-aircraft objects/entities in the airspace zone 108a and updating the airspace zone state accordingly based on this received airspace information.” in ¶99, as per “Entities of a static type, or static entities, are associated with real-world or conceptual static objects that are defined to be static in a geographic location and are generally immovable such as, without limitation, for example terrain features, hills, mountains, buildings, towers, power lines, controlled airspace such as airports or other restricted airspace defined by notice to airmen messages (NOTAMs) and the like, no fly zones, private land and the like and/or as the application demands.” in ¶98)
Claim(s) 12-17 are rejected under 35 U.S.C. 103 as being unpatentable over Parker (WO Pub. No. 2022064166) in view of Evans (US Pub. No. 20190103031) in view of Srivastav (US Pub. No. 20120221305) in further view of Sidiropoulos (US Pub. No. 20200143691).
As per Claim 12, Parker discloses a flight management system (as per Abstract), comprising:
evaluating an airspace design of a subregion of a larger geographic region, (as per Fig. 1A)
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maintaining flight data for the larger geographic region at a monitoring node; (as per Fig. 1B)
receiving at the monitoring node subregion data for the subregion of the larger geographic region, the subregion data being collected by and received from the air navigation service provider; (¶00124 - “The flight orchestration layer includes a plurality of FOCs 204a - 204n, each of the FOCs 204a -204n covering a different one of the airspace regions 202a -202n.”, ¶00125 - “the AMCs of the multiple adjacent airspace zones may be deallocated and the airspace zones merged into a single airspace zone hosted by a corresponding AMC.”, as per FIG. 1B)
updating the flight data by replacing a portion of the flight data with the subregion data to generate integrated flight data; (as per “Given that an entity may receive multiple flight data from multiple flight data sources 321 a, 321 b, 321 c each having a position update/report, a fusion process 328 may be performed to combine and/or fuse multiple position updates/reports.” in ¶166, as per “the fuse process 328 of the AMC 110a or 210a is configured to fuse this flight data or airspace data information together or select the most reliable flight data or airspace data information that the corresponding entity can use.” in ¶166)
the integrated flight data generated from the flight data and the subregion data, (as per “identifying portions of the received flight data associated with each of one or more aircraft of the plurality of aircraft; combining the identified portions of received flight data for said each aircraft into a flight data message including data representative of a single canonical representation of flight data associated with an entity corresponding to said each aircraft; and sending each flight data message to the corresponding AMC for modelling the corresponding airspace zone stat” in ¶117, as per “, geospatial information that may be added to the flight data indicating which airspace zone the in-flight aircraft is traversing. Flight data may be received over a communication network from numerous flight data information sources 205a-205n, each of which may distribute flight data associated with aircraft to each of the corresponding FOCs 204a-204n. Furthermore airspace data/airspace condition data and/or non-flight data associated with the airspace environment… may be ingested from corresponding airspace information/data source(s) 213a-213n and/or flight database 212b/flight services 212 by each of the corresponding set of AMCs 210a-210f connected to the corresponding FOCs 204a-204n and/or flight database 212b of the flight services 212 and the like” in ¶126)
Parker fails to expressly disclose:
receiving, at a monitoring node and from an air navigation service provider, a request for flight simulations of flight plans through the subregion of the larger geographic region, wherein the request specifies a scope of the flight simulations;
performing the flight simulations using the integrated flight data and according to the scope of the flight simulations specified in the request to generate the airspace design;
validating, by the monitoring node, the integrated flight data by comparing the airspace design to a previous airspace design;
generating the flight plans from the flight simulations processed using the flight data
with the flight plans extending within the subregion with the flight plans including entry points into the subregion and exit points out of the subregion;
analyzing the flight plans and determining one or more key performance indicators for the flight plans;
displaying the flight plans and the one or more key performance indicators;
transmitting the flight plans and the one or more key performance indicators to the air navigation service provider to enable aircraft to fly through the subregion.
Evans discloses of flight plan recommendation based on analysis of airspace voxels (as per Abstract), comprising:
performing the flight simulations using the integrated flight data and according to the scope of the flight simulations specified in the request to generate the airspace design; (as per “process 400 can include receiving one or more flight parameters regarding a potential flight plan of an aircraft through a plurality of airspace voxels, including the airspace voxel, during the particular time period (block 430).” in ¶49, as per “For example, UAV management device 260 can receive one or more flight parameters (e.g., from client device 280 via external network 250) regarding a potential flight plan of an aircraft through a plurality of airspace voxels, including the airspace voxel, during the particular time period.” in ¶49, as per “For example, a user can interact with the client device to request a flight plan for a UAV, and the flight plan can include, for example, a departure location and an arrival location, as well as flight parameters” in ¶12)
generating the flight plans from the flight simulations processed using the flight data (as per “the UAV management device can generate a recommendation based on the analysis described above. The recommendation can include, for example, a recommended flight plan for a UAV (as shown), a rejection of a proposed flight plan, an approval of a proposed flight plan, or the like” in ¶15, as per “can include a recommended flight plan. In this case, UAV management device 260 can determine the flight plan based on a best overall score for the flight plan, and/or based on individual scores (e.g., a risk score, a cost score, a time score, a network score, etc.) for the flight plan (e.g., based on combining scores for voxels included in the flight plan)” in ¶74)
with the flight plans extending within the subregion (as per “receive one or more flight parameters regarding a potential flight plan of an aircraft through a plurality of airspace voxels,” in Claim 1) with the flight plans including entry points into the subregion and exit points out of the subregion; (as per “In some implementations, a flight plan can include a departure location (e.g., ground beneath a first voxel), an arrival location (e.g., ground beneath a second voxel), and/or multiple departure locations and arrival locations (for multiple deliveries of packages, for example). “ in ¶50)
analyzing the flight plans and determining one or more key performance indicators for the flight plans; (as per “UAV management device 260 can generate scores for flight plans that take into account one or more of a risk factor (e.g., potential for collision or accident), a cost factor (e.g., energy consumption), a time factor (e.g., time of travel), a network factor (e.g., a risk, cost, or time factor to a network operator with infrastructure that support flight operations), and/or the like.” in ¶57, as per “UAV management device 260 can generate one or more category scores, such as a risk score, a cost score, a time score, a network score” in ¶70)
displaying the flight plans and the one or more key performance indicators; (as per “UAV management device 260 can calculate a voxel score for individual voxels, and can combine voxels along a flight path from a departure location to an arrival location (e.g., a summation of all voxels, an average voxel score, a maximum voxel score, etc.) to calculate an overall score for the flight path. In some implementations, if a score is between thresholds, UAV management device 260 can output the score and/or factors that contributed to the score, and can request operator input as to whether to accept the flight plan.” in ¶58, as per “the UAV management device can provide the recommendation to the client device.” in ¶16)
transmitting the flight plans and the one or more key performance indicators to the air navigation service provider (as per “process 400 can include outputting a recommendation regarding the potential flight plan based on analyzing the one or more flight parameters and the plurality of airspace parameters (block 450).” in ¶71, as per “For example, UAV management device 260 can output a recommendation (e.g., to client device 280 via external network 250) regarding the potential flight plan based on analyzing the one or more flight parameters and the plurality of airspace parameters.” in ¶71) to enable aircraft to fly through the subregion. (as per “UAV management device 260 can output a recommendation (e.g., to client device 280 via external network 250) regarding the potential flight plan based on analyzing the one or more flight parameters and the plurality of airspace parameters.” in ¶71, as per “and can request an update to a flight plan. In this case, UAV management device 260 can receive the request, can execute the analysis, and can return a recommendation to UAV 210 in flight (e.g., via a base station in communication with UAV 210).” in ¶76)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Evans is concerned with airspace design.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the flight management system of Parker with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
Park and Evans fail to expressly disclose:
receiving, at a monitoring node and from an air navigation service provider, a request for flight simulations of flight plans through the subregion of the larger geographic region, wherein the request specifies a scope of the flight simulations;
validating, by the monitoring node, the integrated flight data by comparing the airspace design to a previous airspace design;
Srivastav discloses obtaining selected portions of a movement path simulation over a network, comprising:
receiving, at a monitoring node and from an air navigation service provider, a request for flight simulations of flight plans through the subregion of the larger geographic region, wherein the request specifies a scope of the flight simulations; (as per “selection module configured to compute a total distance of the vehicle movement path simulation from the data and further configured to determine a portion of the total distance to be virtually traversed in simulation based on a request message received from the client computing device via the network, an assembly engine configured to create the portion of the vehicle movement path simulation corresponding to the portion of the total distance to be virtually traversed, and a processor configured to receive the request message from the client computing device and configured to deliver only the portion of the vehicle movement path simulation to the client computing device in response to the request message” in ¶8, as per “receiving an indication of the desired portion of a vehicle movement path to be simulated from a client computing device over the network, retrieving terrain data, weather data, and vehicle performance data associated with one or more geographic positions comprising the portion of the vehicle movement path to be simulated from a data source,” in ¶9)
In this way, Srivastav operates receiving the client’s scoped segment request(¶9). Like Parker and Evans, Srivastav is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker and Evans with the teachings of Srivastav to enable another standard means of receiving requests to process a simulation (¶9).
Parker, Evans, and Srivastav fail to expressly disclose:
validating, by the monitoring node, the integrated flight data by comparing the airspace design to a previous airspace design;
Sidiropoulos discloses of airspace information modeling and design, comprising:
validating, by the monitoring node, (as per “at operation 1030, performing a validation of the airspace design against a first aviation standard, the validation comprising a set of design rules and criteria for evaluation of aircraft performance and safety of operations” in ¶269) the integrated flight data by comparing the airspace design to a previous airspace design; (as per “effective communication of proposed improvement plans to the public, offering visual “as-is” to “proposed” scenario comparisons with complete environmental impact evaluation and noise exposure assessment in particular” in ¶45, as per “Once the user has concluded a design, they are able to save all its parameters and assign a designation to it. AIM enables comparison of multiple scenarios side-by-side, whereas a relevant view snapshot (e.g., map control and vertical profile control for the case of route comparison) from both scenarios are displayed side-by-side” in ¶261, as per “5. Assessment of proposed design scenarios and capability for comparison” in ¶41)
In this way, Sidiropoulos operates to rank flight options by their greenhouse‑gas footprint (Abstract). Like Parker, Evans, and Srivastav, Sidiropoulos is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Evans, and Srivastav with the scenario comparison and validation teachings of Sidiropoulos to validate the integrated flight data by comparing the generated airspace design to a previously stored airspace design, as Sidiropoulos expressly discloses saving airspace designs and enabling "as-is to proposed scenario comparisons" (¶45) as well as side-by-side comparison of saved design scenarios (¶260-¶261) for validation and evaluation purposes. Such a modification would have been an obvious application of known airspace design validation techniques to ensure that newly integrated flight data produces a coherent airspace design consistent with prior design states.
As per Claim 13, the combination Parker, Evans, Srivastav, and Sidiropoulos teaches or suggests all limitations of Claim 12. Parker fails to expressly disclose:
running additional flight simulations using information from the request; and
displaying updated flight plans that include the information from the request.
See Claim 12 for teachings of Evans. Evans further discloses:
running additional flight simulations using information from the request; (as per “the UAV management device can receive one or more flight parameters from the client device. For example, a user can interact with the client device to request a flight plan for a UAV, and the flight plan can include, for example, a departure location and an arrival location, as well as flight parameters.” in ¶12)
displaying updated flight plans that include the information from the request. (as per “the recommendation can include multiple flight plans with an option to select one (e.g., least risky vs. least costly vs. shortest flight time vs. least cost to the network, or some combination thereof, or top 3 scores with risk score, cost score, time score, network score, etc.). Additionally, or alternatively, UAV management device 260 can indicate reasons for the scores or potential risk factors (e.g., high wind, high occupancy, etc.). In some cases, UAV management device 260 can output one or more parameters associated with the voxels so that the user can see conditions along the flight plan.” in ¶75, as per ¶32 & ¶83)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Srivastav, and Sidiropoulos, Evans is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Srivastav, and Sidiropoulos with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
As per Claim 14, the combination Parker, Evans, Srivastav, and Sidiropoulos teaches or suggests all limitations of Claim 12. Parker further discloses ranking the flight plans based on congestion of a subregion airspace that extends over the subregion.
See Claim 12 for teachings of Evans. Evans further discloses ranking the flight plans based on congestion of a subregion airspace that extends over the subregion. (as per “UAV management device 260 can generate scores for flight plans that take into account one or more of a risk factor (e.g., potential for collision or accident), a cost factor (e.g., energy consumption), a time factor (e.g., time of travel), a network factor (e.g., a risk, cost, or time factor to a network operator with infrastructure that support flight operations), and/or the like.” in ¶57, as per “the recommendation can include multiple flight plans with an option to select one (e.g., least risky vs. least costly vs. shortest flight time vs. least cost to the network, or some combination thereof, or top 3 scores with risk score, cost score, time score, network score, etc.)” in ¶75)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Srivastav, and Sidiropoulos, Evans is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Srivastav, and Sidiropoulos with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
As per Claim 15, the combination Parker, Evans, Srivastav, and Sidiropoulos teaches or suggests all limitations of Claim 12. Parker further discloses of receiving the subregion data in Aeronautical Information Exchange Model (AIXM) format and integrating the subregion data in the flight data. (as per “The one or more other flight data information sources may further include, without limitation, for example at least one from the group of: another aircraft; a radar detecting position of said aircraft; All Purpose Structured Eurocontrol Surveillance Information Exchange (ASTERIX) air traffic services information; airspace surveillance data associated with one or more of said plurality of aircraft; automatic dependent surveillance broadcast, ADS-B, data associated with one or more of said aircraft; flight planning services configured for providing flight plans of one or more of the aircraft of the plurality of aircraft; any other standard for exchange of air traffic services information and the like.” in ¶94)
As per Claim 16, the combination Parker, Evans, Srivastav, and Sidiropoulos teaches or suggests all limitations of Claim 13. Parker fails to expressly disclose generating the flight plans for Free Route Airspace within the airspace of the subregion.
See Claim 13 for teachings of Evans. Evans further discloses generating the flight plans for Free Route Airspace within the airspace of the subregion. (as per “the recommended flight plan can provide information to instruct and/or control the UAV to depart from voxel B, and then to proceed to voxel D rather than voxel A because voxel A has a high occupancy. Continuing with the example, the recommended flight plan can provide information to instruct and/or control the UAV to avoid voxel F (e.g., to prevent violation of a noise ordinance associated with voxel F), and to proceed from voxel D to voxel C to voxel E to voxel G to the arrival location at voxel H.” in ¶16, as per “UAV management device can analyze a large quantity (e.g., hundreds, thousands, millions, etc.) of data points for a large quantity of UAVs to generate recommended flight plans for one or more UAVs” in ¶17)
In this way, Evans operates to generate airspace voxels (¶9) and analyze data to generate recommended flight plans (¶17). Like Parker, Srivastav, and Sidiropoulos, Evans is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Srivastav, and Sidiropoulos with flight plan recommendation as taught by Evans to enable another standard means of generating flight plans (¶17). Such modification also allows the system to employ voxels, 3-dimensional portions of airspace (¶8), and subsequently generate flight plans throughout the plurality of voxels (Claim 1).
As per Claim 17, the combination Parker, Evans, Srivastav, and Sidiropoulos teaches or suggests all limitations of Claim 12. Parker further discloses:
maintaining the flight data for the larger geographic region at the monitoring node with the navigation data being devoid of any data from the subregion; (as per “Given that an entity may receive multiple flight data from multiple flight data sources 321 a, 321 b, 321 c each having a position update/report, a fusion process 328 may be performed to combine and/or fuse multiple position updates/reports.” in ¶166, as per “the fuse process 328 of the AMC 110a or 210a is configured to fuse this flight data or airspace data information together or select the most reliable flight data or airspace data information that the corresponding entity can use.” in ¶166, as per “the AMCs of the multiple adjacent airspace zones may be deallocated and the airspace zones merged into a single airspace zone hosted by a corresponding AMC.” in ¶125, as per “incoming flight data and/or airspace data and the like that is being received from the flight data source(s) may be queued/buffered.” in ¶112, as per FIG. 1B)
generating the integrated flight data by adding the subregion data to the flight data (as per “Given that an entity may receive multiple flight data from multiple flight data sources 321 a, 321 b, 321 c each having a position update/report, a fusion process 328 may be performed to combine and/or fuse multiple position updates/reports” in ¶166”, as per “the fuse process 328 of the AMC 110a or 210a is configured to fuse this flight data or airspace data information together or select the most reliable flight data or airspace data information that the corresponding entity can use.” in ¶166, as per “the AMCs of the multiple adjacent airspace zones may be deallocated and the airspace zones merged into a single airspace zone hosted by a corresponding AMC.” in ¶125)
Claim(s) 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Parker (WO Pub. No. 2022064166) in view of Evans (US Pub. No. 20190103031) in view of Kaivanto (NPL Title: Rank-order concordance among conflicting emissions estimates for informing flight choice, Year: 2017) in further view of Jiong (CN Pub. No. 108961843).
As per Claim 9, the combination of Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker, Evans, Kaivanto, and Sidiropoulos fail to expressly disclose transmitting the flight data of the geographic region airspace to the monitoring node in ARINC 424 format.
Jiong discloses a system and method based on track running technology (as per Abstract), comprising transmitting the flight data of the geographic region airspace to the monitoring node in ARINC 424 format. (¶0080 “In addition, the airborne FMS also includes other required functions defined by ARINC702A”)
In this way, Jiong operates to simulate the airspace (Abstract). Like Parker, Evans, Kaivanto, and Sidiropoulos, Jiong is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Evans, Kaivanto, and Sidiropoulos with the airspace simulation of Jiong to enable another standard means of modelling and validating airspace plans (¶76, Abstract).
As per Claim 10, the combination of Parker, Evans, Kaivanto, and Sidiropoulos teaches or suggests all limitations of Claim 1. Parker, Evans, Kaivanto, and Sidiropoulos fail to expressly disclose transmitting a flight data validation report to the air navigation service provider after integrating the subregion data with the flight data.
Jiong discloses a system and method based on track running technology (as per Abstract), comprising transmitting a flight data validation report to the air navigation service provider after integrating the subregion data with the flight data. (as per “verifying the validity of flight plans, modifying flight plans, switching to backup flight plans, etc.” in ¶76, “the simulation data of the airspace simulation system and the air traffic control platform simulation system of the ground-side simulation system are mutually transmitted with the simulation data of the airborne flight management simulation system and the aircraft simulation system of the airborne -side simulation system through the air-ground data link simulation system” in ¶28, as per “The main functions include: providing air traffic management functions including airport surface management, tower control, approach control, and area control; providing a set of ANSP decision support tools that support surface management ” in ¶58)
In this way, Jiong operates to simulate the airspace (Abstract). Like Parker, Evans, Kaivanto, and Sidiropoulos, Jiong is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Evans, Kaivanto, and Sidiropoulos with the airspace simulation of Jiong to enable another standard means of modelling and validating airspace plans (¶76, Abstract).
Claim(s) 18 is rejected under 35 U.S.C. 103 as being unpatentable over Parker (WO Pub. No. 2022064166) in view of Evans (US Pub. No. 20190103031) in view of Srivastav (US Pub. No. 20120221305) in view of Sidiropoulos (US Pub. No. 20200143691) in further view of Jiong (CN Pub. No. 108961843).
As per Claim 18, the combination Parker, Evans, Srivastav, and Sidiropoulos teaches or suggests all limitations of Claim 12. Parker, Evans, Srivastav, and Sidiropoulos fail to expressly disclose transmitting the integrated flight data to the monitoring node in ARINC 424 format.
Jiong discloses a system and method based on track running technology (as per Abstract), comprising transmitting the integrated flight data to the monitoring node in ARINC 424 format. (as per “In addition, the airborne FMS also includes other required functions defined by ARINC702A” in ¶80)
In this way, Jiong operates to simulate the airspace (Abstract). Like Parker, Evans, Srivastav, and Sidiropoulos, Jiong is concerned with aircraft.
It would have been obvious for one of ordinary skill in the art before the effective filing date to have modified the system(s) of Parker, Evans, Srivastav, and Sidiropoulos with the airspace simulation of Jiong to enable another standard means of modelling and validating airspace plans (¶76, Abstract).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Li (CN Pub. No. 111581780) discloses airport group airspace simulation modeling and verification method and device under complex airspace scene.
D’Alto (US Pub. No. 20160371989) discloses a computer-implemented method and system for estimating impact of new operational conditions in a baseline air traffic scenario.
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/T.R.R./Examiner, Art Unit 3658
/Ramon A. Mercado/Supervisory Patent Examiner, Art Unit 3658