DETAILED ACTION
Status of Claims
This Office action is in response to the amendment filed on 11/26/2025. Claims 9-20 have been canceled, and new claims 21-33 have been added. Claims 1-8 and 21-33 are currently pending and are presented for examination.
Response to Amendment/Arguments
The amendment filed 11/26/2025 has been entered and applicant’s arguments filed 11/26/2025 have been fully considered.
Regarding objections:
Applicant has argued that the objections to the drawings, specification, and claims have been overcome by the filed amendment. The examiner agrees and has withdrawn the objections accordingly.
Regarding rejections under 35 U.S.C. § 101:
Applicant has argued that the claim rejections under 35 U.S.C. § 101 have been overcome by the filed amendment. The examiner agrees and has withdrawn these rejections accordingly.
Regarding rejections under 35 U.S.C. §§ 102 and 103:
Applicant’s arguments regarding the prior art rejections are moot in view of the new grounds of rejection under 35 U.S.C. § 103 which are necessitated by the filed amendment.
Claim Rejections - 35 USC § 103
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.
Claims 1-6, 8, and 21-33 are each rejected under 35 U.S.C. 103 as being unpatentable over Rostamzadeh et al. (US 2020/0388166 A1), hereinafter referred to as Rostamzadeh, in view of Benedek (US 2023/0394981 A1).
Regarding claim 1:
Rostamzadeh discloses the following limitations:
“A method of assigning an electric vertical takeoff and landing (eVTOL) aircraft to a skylane, the method comprising: accessing trip request data defining a trip request for aerial transport at a particular travel time from an origin location to a destination location within a particular geographic area.” (Rostamzadeh ¶ 4 discloses that “on-demand aviation” can be used with electric VTOL aircraft. Further, Rostamzadeh ¶ 146: “Some embodiments of operation 1222 determine an origin and destination of an aircraft flight. These embodiments then determine a plurality of possible routes between the origin and destination. Each of the plurality of possible routes includes a plurality of different geographic regions through which the aircraft travels to reach the destination from the origin location.” Also, Rostamzadeh ¶ 149 discloses that “aerial vehicle constraints” can include operating constraints such as take-off times, in-flight travel times, and landing times.)
“accessing skylane network data indicative of a plurality of skylanes for eVTOL aircraft travel in the particular geographic area; computing a subset of the plurality of skylanes as candidate skylanes for servicing the trip request.” (Rostamzadeh ¶ 97 and FIGS. 7A-7B disclose a map showing a network of sky lanes, where “A sky lane defines how air traffic may be routed through the geographic region shown in the image.” Also, Rostamzadeh ¶ 67: “motion planning system 226 can evaluate cost functions and/or one or more reward functions for each of one or more candidate motion plans for the aerial vehicle 200. For example, the cost function(s) can describe a cost (e.g., over time) of adhering to a particular candidate motion plan while the reward function(s) can describe a reward for adhering to the particular candidate motion plan.”)
“wherein the candidate skylanes are determined based on a route assessment configured to evaluate an operating constraint associated with respective skylanes relative to parameter data predicted for the particular geographic area at the particular travel time.” (Rostamzadeh ¶ 46: “Allocation of these routes/sky lanes is determined by the mobility network servers 110 based on environmental acceptance (e.g., noise), weather, airspace deconfliction, and operational relevancy.” Further, Rostamzadeh ¶¶ 67-68: “the cost function(s) can describe a cost (e.g., over time) of adhering to a particular candidate motion plan while the reward function(s) can describe a reward for adhering to the particular candidate motion plan. … Thus, given information about the current locations and/or predicted future locations/trajectories of objects, the motion planning system 226 can determine a total cost (e.g., a sum of the cost(s) and/or reward(s) provided by the cost function(s) and/or reward function(s)) of adhering to a particular candidate pathway.”)
“computing a selected skylane from the candidate skylanes for servicing at least a portion of the trip request.” (Rostamzadeh ¶ 68: “The motion planning system 226 can select or determine a motion plan for the aerial vehicle 200 based at least in part on the cost function(s) and the reward function(s). For example, the motion plan that minimizes the total cost can be selected or otherwise determined.”)
“generating a trip assignment for deployment of an eVTOL aircraft from the origin location into the selected skylane.” (Rostamzadeh ¶ 101: “particular aerial vehicles can be selected and assigned to routes.” Also, Rostamzadeh ¶ 70: “motion planning system 226 can provide the motion plan to vehicle control systems 228 to execute the motion plan.”)
“computing a refined subset of the plurality of skylanes as refined candidate skylanes for servicing the trip request, wherein the refined candidate skylanes are determined based on a refined route assessment configured to evaluate the operating constraint associated with respective skylanes … computing a selected skylane from the refined candidate skylanes for servicing at least a portion of the trip request.” (Rostamzadeh ¶¶ 67-68: “the cost function(s) can describe a cost (e.g., over time) of adhering to a particular candidate motion plan while the reward function(s) can describe a reward for adhering to the particular candidate motion plan. … The motion planning system 226 can select or determine a motion plan for the aerial vehicle 200 based at least in part on the cost function(s) and the reward function(s). … In some implementations, the motion planning system 226 can be configured to iteratively update the motion plan for the aerial vehicle 200 as new sensor data is obtained from the sensors 218.”)
“and generating a refined trip assignment for deployment of the eVTOL aircraft from the origin location into the selected skylane from the refined candidate skylanes.” (Rostamzadeh ¶ 70: “motion planning system 226 can provide the motion plan to vehicle control systems 228 to execute the motion plan.”)
The following limitations are not specifically disclosed by Rostamzadeh, but are taught by Benedek:
“accessing real-time parameter data comprising data descriptive of a current fuel or charge level of the eVTOL aircraft.” (Benedek ¶ 139: “The remaining amount of the resources necessary for the flight of the flying objects will be described below as the remaining amount of the battery, but other items such as the remaining amount of the fuel may be used.” Further, Benedek ¶ 328: “data acquisition unit 32 of the flight management apparatus 30 may acquire real-time data of a flying object using a communication protocol from the flying object before taking off from a departure point. The real-time data is information about the state(s) of the flying object, including, for example, at least one of the battery level, the engine state, and the maintenance state of the flying object (for example, the presence or absence of an automobile inspection within a predetermined period).”)
“the refined candidate skylanes are determined based on a refined route assessment configured to evaluate the operating constraint associated with respective skylanes relative to the real-time parameter data.” (Benedek ¶ 143: “The route generation unit 33 may generate a flight route of the flying object by using the reservation state of the space cell C stored in the memory 31 so that other flying objects do not overlap the reserved space cell.” Further, Benedek ¶ 145: “it may be desirable to set a route other than the shortest distance depending on the conditions such as the battery level of the flying object and the weather. … when the remaining battery of the flying object is less than a predetermined value, the route generation unit 33 may calculate the battery consumption of each of the candidate flight routes and select the flight route with the lowest battery consumption.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the method of Rostamzadeh by considering real-time battery or fuel data when determining appropriate candidate routes as taught by Benedek with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do upon recognizing that some candidate routes with longer flight distances or flight times may result in the aircraft running out of charge or fuel before reaching the destination; filtering the candidate routes based on battery or fuel level would help prevent potential damage to the aircraft and avoid a need for refueling the aircraft in the middle of the route.
Regarding claim 2:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh also teaches the following limitations:
“wherein: the plurality of skylanes are respectively depicted as a directed graph representation of nodes and edges.” (Rostamzadeh ¶¶ 15-16 and FIG. 7A-7B shown below: “FIG. 7A shows node optimization based on loudness. … FIG. 7B shows selection of a sky lane based on loudness data.”)
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“and computing a selected skylane from the candidate skylanes for servicing at least a portion of the trip request comprises determining a path along edges in the directed graph representation that minimize a cost function between a node corresponding to the origin location and a node corresponding to the destination location.” (Rostamzadeh ¶ 68: “the motion planning system 226 can determine a total cost (e.g., a sum of the cost(s) and/or reward(s) provided by the cost function(s) and/or reward function(s)) of adhering to a particular candidate pathway. The motion planning system 226 can select or determine a motion plan for the aerial vehicle 200 based at least in part on the cost function(s) and the reward function(s).” Further, Rostamzadeh ¶¶ 97 and 146-147: “FIG. 7B shows selection of a sky lane based on loudness data,” and “Some embodiments of operation 1222 determine an origin and destination of an aircraft flight. These embodiments then determine a plurality of possible routes between the origin and destination. Each of the plurality of possible routes includes a plurality of different geographic regions through which the aircraft travels to reach the destination from the origin location. Some of the embodiments of process 1200 generate predicted background noise in each of these geographic regions, based on dynamic and static feature data of each of the respective regions. … Some embodiments then select one of the plurality of routes based on the predicted background noise.”)
Regarding claim 3:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh additionally teaches “wherein computing a selected skylane from the candidate skylanes for servicing at least a portion of the trip request at the particular travel time is based on historical trip data indicative of previous trips between the origin location and the destination location.” (Rostamzadeh ¶ 139: “Some of the sensors are configured to collected weather data, such as the temperature, dewpoint, humidity, wind speed, wind direction, and other weather data during multiple time periods. The detected time varying loudness and weather data is correlated according to a time at which the loudness and weather information is collected. Thus, the historical data describes, over a plurality of time periods, weather data, traffic data, and noise information for a particular region.”)
Regarding claim 4:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh also teaches the following limitations:
“further comprising: computing a plurality of candidate aircraft from a fleet of aircraft for servicing the trip request at the particular travel time, wherein the plurality of candidate aircraft are determined based on an aircraft assessment configured to evaluate an operating constraint associated with respective aircraft of the fleet of aircraft relative to parameter data for the particular geographic area at the particular travel time.” (Rostamzadeh ¶ 101: “the aerial vehicle fleet may include aerial vehicles of different types, makes, models, sizes, and so forth. As such, certain types of aerial vehicles within the aerial fleet may generate different levels of noise/loudness as the vehicle takes-off, lands, and/or traverses a route (e.g., due to differences in propulsion systems, payload capacity, fuel types, etc.). … the noise map data can indicate the predicted loudness at locations along routes within a geographic region (e.g., a background noise layer), which can allow for the determination of how much additional noise/loudness can be added by an operating aerial vehicle (e.g., an aerial vehicle noise layer) to remain below an acceptable level of loudness.”)
“and computing a selected aircraft from the plurality of candidate aircraft for servicing the trip request at the particular travel time; wherein generating the trip assignment for deployment of the eVTOL aircraft from the origin location into the selected skylane is configured for deployment of the selected aircraft.” (Rostamzadeh ¶ 101: “Based on such a determination, particular aerial vehicles can be selected and assigned to routes in order to maintain a total noise level below the acceptable level of loudness.”)
Regarding claim 5:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1, and Rostamzadeh further teaches the method “further comprising: computing a departure time for deployment of the eVTOL aircraft from the origin location into the selected skylane, the departure time determined based on the particular travel time and updated parameter data associated with the plurality of skylanes at the particular travel time.” (Rostamzadeh ¶ 99: “The noise map data can also, or alternatively, be used to determine one or more operating constraints of an aerial vehicle. For instance, time constraints identifying take-off times, flight travel times, landing times, times for a first take-off/landing of the day, times for a last take-off/landing of the day, etc. can be determined based on the noise map data. In particular, the noise map data can provide the predicted loudness at various times of the day and, thus, allow for flight time schedules to be generated to maintain an acceptable level of loudness.” Also, Rostamzadeh ¶ 68: “the motion planning system 226 can be configured to iteratively update the motion plan for the aerial vehicle 200 as new sensor data is obtained from the sensors 218.”)
Regarding claim 6:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh also teaches “wherein the operating constraint associated with respective skylanes of the plurality of skylanes comprises a type of eVTOL aircraft designated for travel on the respective skylanes of the plurality of skylanes.” (Rostamzadeh ¶ 101: “the aerial vehicle fleet may include aerial vehicles of different types, makes, models, sizes, and so forth. As such, certain types of aerial vehicles within the aerial fleet may generate different levels of noise/loudness as the vehicle takes-off, lands, and/or traverses a route (e.g., due to differences in propulsion systems, payload capacity, fuel types, etc.). The aerial vehicle operating noise/loudness levels may be acquired and stored (e.g., via the aerial vehicle manufacturer/vendor), measured by sensors as the aerial vehicle operates, and/or calculated based on a vehicle model. As described herein, the noise map data can indicate the predicted loudness at locations along routes within a geographic region (e.g., a background noise layer), which can allow for the determination of how much additional noise/loudness can be added by an operating aerial vehicle (e.g., an aerial vehicle noise layer) to remain below an acceptable level of loudness. Based on such a determination, particular aerial vehicles can be selected and assigned to routes in order to maintain a total noise level below the acceptable level of loudness.”)
Regarding claim 8:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh also teaches “wherein the operating constraint associated with respective skylanes of the plurality of skylanes comprises a noise limit defining a threshold visual noise level or a threshold audible noise level established for the particular geographic area.” (Rostamzadeh ¶ 29: “noise predictions for the geographic region may be used to determine whether to route an aircraft through the region, at what altitude to route the aircraft, and/or at what times.” Additionally, Rostamzadeh ¶ 80: “The aircraft flight's altitude is also in some cases selected based on the background noise loudness predicted along a route, with less noisy routes (below a first predefined noise threshold) causing the aircraft altitude to be set to a higher value (above a first predefined altitude threshold) while more noisy routes (above a second predefined noise threshold) result in a lower altitude (below a second predefined altitude threshold).” This at least teaches the operating constraint comprising a noise limit defining a “threshold audible noise level established for the particular geographic area” as claimed.)
Note that under the broadest reasonable interpretation (BRI) of claim 8, consistent with the specification, the operating constraint comprising “a noise limit defining a threshold visual noise level or a threshold audible noise level established for the particular geographic area” is treated as an alternative limitation. Applicant has elected to use the word “or” in the claim language, and therefore, the BRI covers the scenario in which only one of the limitations applies. Accordingly, while only “a threshold audible noise level established for the particular geographic area” has been addressed here, the claim is still rejected in its entirety.
Regarding claim 21:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Benedek also teaches “wherein the operating constraint associated with respective skylanes of the plurality of skylanes comprises a weather condition limit defining an acceptable level of a temperature, a pressure, a wind condition, or a visibility condition established for the particular geographic area.” (Benedek ¶ 418: “when a strong wind with a wind velocity equal to or greater than a predetermined value is blowing in the area A9, the airport air traffic control unit can set space cell(s) in a space where the approach to the airport is judged to be dangerous due to the strong wind as a non-flyable area.” This at least teaches the weather condition limit defining an acceptable level of a wind condition established for the particular geographic area as claimed.)
Note that under the broadest reasonable interpretation (BRI) of claim 21, consistent with the instant specification, the operating constraint comprising “a weather condition limit defining an acceptable level of a temperature, a pressure, a wind condition, or a visibility condition established for the particular geographic area” is treated as an alternative limitation. Applicant has elected to use the word “or” in the claim language, and therefore, the BRI covers the scenario in which only one of the limitations applies. Accordingly, while only the “acceptable level of … a wind condition… established for the particular geographic area” has been addressed here, the claim is still rejected in its entirety.
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the method of Rostamzadeh by incorporating an operational constraint that is based on a weather condition limit defining an acceptable level of a weather condition such as wind as taught by Benedek with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this because Benedek ¶ 418 teaches that winds that are too strong can create dangerous flying conditions for the aircraft. A person having ordinary skill in the art would have recognized that the use of acceptable levels of certain weather conditions like wind would provide an objective way to ensure flight safety for the aircraft and for any occupants.
Regarding claim 22:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh also teaches “wherein computing a subset of the plurality of skylanes as candidate skylanes for servicing the trip request comprises: implementing a first computing iteration based on predicted parameter data for the particular geographic area at the particular travel time; and implementing a second skylane iteration based on real-time parameter data for the particular geographic area at the particular travel time.” (Rostamzadeh ¶ 28: “Dynamic feature information is also collected via deployment of a variety of sensors. Some sensors are configured to collect weather data in a region, including, for example, one or more of temperature, dewpoint, humidity, wind speed, wind direction, pressure, or other weather data. Other sensors collect noise information within the region. For example, noise sensors are configured to collect time varying loudness data on a plurality of frequencies. Other sensors record traffic amount and volume information.” Further, Rostamzadeh ¶ 68: “the motion planning system 226 can be configured to iteratively update the motion plan for the aerial vehicle 200 as new sensor data is obtained from the sensors 218.”)
Regarding claim 23:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh also teaches “wherein the parameter data comprises location parameter data defining takeoff and landing paths for other aircraft operating in the particular geographic area.” (Rostamzadeh ¶ 43: “mobility network servers 110 is also coupled to an unmanned aerial vehicle traffic management system (UTM) 108, which operates to provide aircraft traffic management and de-confliction services to the aerial vehicle fleet 102.” Also, Rostamzadeh ¶ 46: “Allocation of these routes/sky lanes is determined by the mobility network servers 110 based on environmental acceptance (e.g., noise), weather, airspace deconfliction, and operational relevancy.”)
Regarding claim 24:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh additionally teaches “wherein the parameter data comprises noise level data defining a visual noise level or an audible noise level determined for the particular geographic area.” (Rostamzadeh ¶ 29: “noise predictions for the geographic region may be used to determine whether to route an aircraft through the region, at what altitude to route the aircraft, and/or at what times.” Also, Rostamzadeh ¶ 80: “The aircraft flight's altitude is also in some cases selected based on the background noise loudness predicted along a route, with less noisy routes (below a first predefined noise threshold) causing the aircraft altitude to be set to a higher value (above a first predefined altitude threshold) while more noisy routes (above a second predefined noise threshold) result in a lower altitude (below a second predefined altitude threshold).” This at least teaches the parameter data comprising noise level data defining “an audible noise level determined for the particular geographic area” as claimed.)
Note that under the broadest reasonable interpretation (BRI) of claim 24, consistent with the specification, the parameter data comprising “noise level data defining a visual noise level or an audible noise level determined for the particular geographic area” is treated as an alternative limitation. Applicant has elected to use the word “or” in the claim language, and therefore, the BRI covers the scenario in which only one of the limitations applies. Accordingly, while only the “audible noise level determined for the particular geographic area” has been addressed here, the claim is still rejected in its entirety.
Regarding claim 25:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh also teaches “wherein the parameter data comprises weather data defining of at least one of a temperature, a pressure, a wind condition, or a visibility condition determined for the particular geographic area.” (Rostamzadeh ¶ 28: “Some sensors are configured to collect weather data in a region, including, for example, one or more of temperature, dewpoint, humidity, wind speed, wind direction, pressure, or other weather data.” Further, Rostamzadeh ¶ 46: “Allocation of these routes/sky lanes is determined by the mobility network servers 110 based on environmental acceptance (e.g., noise), weather, airspace deconfliction, and operational relevancy.” This at least teaches the parameter data comprising weather data defining a temperature, a pressure, and/or a wind condition as claimed.)
Note that under the broadest reasonable interpretation (BRI) of claim 25, consistent with the specification, the parameter data comprising “weather data defining of at least one of a temperature, a pressure, a wind condition, or a visibility condition determined for the particular geographic area” is treated as an alternative limitation. Applicant has elected to use the phrase at least one” in the claim language, and therefore, the BRI covers the scenario in which only one of the limitations applies. Accordingly, while only the temperature, pressure, and wind condition have been addressed here, the claim is still rejected in its entirety.
Regarding claim 26:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh additionally teaches “wherein the parameter data comprises location data from an application associated with a pilot or a passenger currently traveling on a particular skylane of the plurality of skylanes.” (Rostamzadeh ¶ 44: “The acquisition of data for traffic monitoring, for example, by the aerial vehicle fleet 102 may be based on the aerial vehicles fly trips predetermined and/or optimized by an UTM network. Connection to the UTM 108 is facilitated across multiple communications frequencies as needed for operation. Onboard telemetry of vehicles in the aerial vehicle fleet 102 is supplemented with GPS data in addition to other communication streams (GPS, 5G, etc.).” Also, Rostamzadeh ¶ 164: “The applications 1320 include built-in applications 1340 and/or third-party applications 1342. Examples of representative built-in applications 1340 may include… a location application… In a specific example, the third-party application 1342 (e.g., an application developed using the Android™ or iOS™ software development kit (SDK) by an entity other than the vendor of the particular platform) may be mobile software running on a mobile operating system such as iOS™, Android™ Windows® Phone, or other computing device operating systems.”)
Regarding claim 27:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh additionally teaches the method “further comprising: accessing updated parameter data at a time subsequent to the generating of the trip assignment; computing the selected skylane from the candidate skylanes for servicing at least a portion of the trip request at the particular travel time based on the updated parameter data; and generating an updated trip assignment for deployment of the eVTOL aircraft from the origin location into the selected skylane.” (Rostamzadeh ¶ 28: “Dynamic feature information is also collected via deployment of a variety of sensors. Some sensors are configured to collect weather data in a region, including, for example, one or more of temperature, dewpoint, humidity, wind speed, wind direction, pressure, or other weather data. Other sensors collect noise information within the region. For example, noise sensors are configured to collect time varying loudness data on a plurality of frequencies. Other sensors record traffic amount and volume information.” Additionally, Rostamzadeh ¶ 68: “the motion planning system 226 can be configured to iteratively update the motion plan for the aerial vehicle 200 as new sensor data is obtained from the sensors 218.”)
Regarding claim 28:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” and Rostamzadeh also teaches the method “further comprising: providing deployment instructions to initiate takeoff of the eVTOL aircraft into the selected skylane to fulfill the trip assignment.” (Rostamzadeh ¶¶ 70-71: “The motion planning system 226 can provide the motion plan to vehicle control systems 228 to execute the motion plan. … A throttle control system 234 is configured to receive all or part of the motion plan and generate a throttle command.”)
Regarding claim 29:
Rostamzadeh discloses “One or more non-transitory computer-readable media storing instructions that are executable by one or more processors to perform operations.” (See Rostamzadeh ¶ 72: “The aerial vehicle autonomy system 212 includes one or more computing devices, such as the computing device 202 which may implement all or parts of the perception system 220, the prediction system 224, the motion planning system 226 and/or the pose system 222. The example computing device 202 can include one or more processors 204 and one or more memory devices (collectively referred to as memory 206). … The memory 206 can include one or more non-transitory computer-readable storage mediums.”)
The remaining limitations of claim 29 are taught by the combination of Rostamzadeh and Benedek using the same rationale applied to claim 1 above, mutatis mutandis.
Regarding claims 30-31:
Claims 30-31 are rejected using the same rationale, mutatis mutandis, applied to claims 2-3 above, respectively.
Regarding claim 32:
Rostamzadeh discloses “A computing system, comprising: one or more processors; and one or more non-transitory computer-readable media storing instructions that are executable by the one or more processors to perform operations.” (Rostamzadeh ¶ 72: “aerial vehicle autonomy system 212 includes one or more computing devices, such as the computing device 202 which may implement all or parts of the perception system 220, the prediction system 224, the motion planning system 226 and/or the pose system 222. The example computing device 202 can include one or more processors 204 and one or more memory devices (collectively referred to as memory 206). … The memory 206 can include one or more non-transitory computer-readable storage mediums.”)
The remaining limitations of claim 32 are taught by the combination of Rostamzadeh and Benedek using the same rationale applied to claim 1 above, mutatis mutandis.
Regarding claim 33:
Claim 33 is rejected with the same rationale applied to claim 2 above, mutatis mutandis.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Rostamzadeh in view of Benedek as applied to claim 1 above, and further in view of Chan et al. (US 2016/0117929 A1), hereinafter referred to as Chan.
Regarding claim 7:
The combination of Rostamzadeh and Benedek teaches “The method of claim 1,” but does not specifically teach “wherein the operating constraint associated with respective skylanes of the plurality of skylanes comprises a speed for eVTOL aircraft designated for travel on the respective skylanes of the plurality of skylanes.” However, Chan does teach this limitation. (Chan ¶ 226 discloses that a “management system in the administration of the airspace may establish maximum and minimum speed/regulated speed limits for UAV/drone craft in flyway segments/ lanes to ensure efficient traffic flow through the airspace; rates for use of a flyway segment/lane may be established with reference to speed limits and other factors such as occupancy as well as the rights/priority and route assigned to the UAV/drone craft. According to an exemplary embodiment, UAV/drone craft would be routed by the management system to travel in flyway segments/lanes according to capability such as speed of travel of the UAV/drone craft.” Further, Chan ¶ 151 discloses that “the system may facilitate the operation of any present or future type/configuration of UAV/drone craft in the airspace,” and Chan ¶ 243 teaches use with “vertical take-off/landing craft.”)
Before the effective filing date of the claimed invention, it would have been obvious to a person having ordinary skill in the art to modify the method that is disclosed by the combination of Rostamzadeh and Benedek by routing aircraft to flyway lanes based on speed limits as taught by Chan with a reasonable expectation of success. A person having ordinary skill in the art could have been motivated to do this because Chan ¶ 226 teaches that this can help “to ensure efficient traffic flow through the airspace” while complying with regulatory requirements.
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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/Madison R. Inserra/Primary Examiner, Art Unit 3662
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