DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
This first non-final action is in response to applicant's original filing on Feb. 26, 2026. Claims 1-10 and 21-29 are pending and have been considered as follows.
Response to Arguments
Applicant’s amendments/arguments with respect to the rejections to claims under 35 U.S.C 101 have been fully considered and are persuasive. Therefore, the rejections to claims under 35 U.S.C 101 have been withdrawn.
Applicant’s amendments/arguments with respect to claim(s) 1-20 under 35 U.S.C 103 have been fully considered but are moot because the new ground of rejection does not rely on any reference for any teaching or matter specifically challenged in the argument.
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 3-6, 9-10, 21-26, 28 are rejected under 35 U.S.C. 103 as being obvious over Shi (US 20250095169 A1) in view of Basalamah (US 20160078756 A1)
Regarding Claim 1 , Shi teaches a method that is computer implemented and is for using aerial image information (abstract), the method comprising:
dynamically determining, by a controller that comprises one or more hardware processing circuits and is associated with an autonomous vehicle, one or more downloading parameters of a downloading of a batch of aerial image signatures (Shi [0013]-[0015], Satellite image guided geo-localization uses images acquired by sensors included in a vehicle to determine a high-definition pose with respect to satellite images without requiring predetermined high-definition (HD) maps. [0036] FIG. 2 is a diagram of a satellite image 200. Satellite image 200 can be a map downloaded to the computing device 115 in the vehicle 110 via the network 130, e.g., from a source such as GOOGLE maps. Satellite image 200 includes roadways 202, buildings 204, indicated by rectilinear shapes, and foliage 206, indicated by irregular shapes. [0058] (parameter) Satellite image 403 can be selected to include an estimated three DoF pose 302; [0038] High-definition maps typically require extensive mapping efforts and large amounts of computer resources to produce and store the HD maps, along with large amounts of network bandwidth ((parameter)) typically consumed to download the HD maps to vehicles 110, not to mention the large amount of computer memory typically required to store the maps in computing devices 115 included in vehicles. Satellite image guided pose refinement techniques described herein use 3D feature points determined based on video images acquired by video cam-eras included in a vehicle 110 to determine a high-definition three DoF pose for a vehicle 110 based on satellite images without requiring large amounts of computer processing, networking, and/or memory resources typically required to produce, transmit, and store HD maps; it is well established that anonymous vehicle may download images/maps; e.g. US 20210311474 A1 );
controlling, by the controller, the downloading of the batch of the aerial image signatures to a memory unit associated with the autonomous vehicle; determining a location of the autonomous vehicle based on the aerial image signatures and on vehicle sensed information signatures ([0013]-[0014]; [0074]; Fig. 5 and corresponding paragraphs);
determining an autonomous driving operation based on the location of the autonomous vehicle ([0076] At block 806 computing device 115 uses the high-definition estimated three DoF pose to determine a vehicle path for the vehicle 110. The vehicle can operate on a roadway based on a vehicle path by determining commands to direct the vehicle's propulsion (e.g., powertrain), braking, and steering subsystems to operate the vehicle so as to travel along the path), and
autonomous driving the autonomous vehicle by autonomously controlling at least one of a speed, direction of propagation or an acceleration of the autonomous vehicle ([0076] The vehicle can operate on a roadway based on a vehicle path by determining commands to direct the vehicle's propulsion (e.g., powertrain), braking, and steering subsystems to operate the vehicle so as to travel along the path).
Shi does not explicitly teach but Basalamah teaches the specific limitations of wherein the dynamically determining comprises repeating the determining at multiple point in time during a driving session of the autonomous vehicle, wherein a duration between one point in time to another is based on a complexity of an environment in which the autonomous vehicle is located during the driving session (Basalamah, Fig. 2 and corresponding paragraphs including at least [0045] With the available cumulative collected about the traffic expected sites, the backend server 102 can detect the flow of people and infer the changes in routes, and then auto update the maps automatically; [0044] In step 212, the processing circuitry transmits(download) the updated traffic map back to the wireless devices 110 and/or monitors 108; [0053] the backend server 102 analyzes the image to determine the number of cars and/or pedestrians within the image).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, matching a ground view image and an aerial view image, as taught by Shi, repeating the determining at multiple point in time during a driving session of the autonomous vehicle, as taught by Basalamah, as Shi and Basalamah are directed to downloading images to vehicles (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using repeating the determining at multiple point in time during a driving session of the autonomous vehicle and predictably applied it to Shi’s teaching to update traffic maps and estimate crowds instantaneously to reflect those real-time change.
Regarding claim 10 please see the rejection above with regarding Claim 1.
Regarding claim 3, Shi teaches wherein determining of the location of the autonomous vehicle comprises the downloaded batch of aerial image signatures with the vehicle sensed information signatures (Fig. 5 and corresponding paragraphs).
Regarding claim 4, Shi teaches the selectively determining is further based on, at least in part, an availability of localization resources of the autonomous vehicle (Fig. 5 and corresponding paragraphs).
Regarding claim 5, Shi teaches wherein the localization resources comprises a mapping resource configured to map aerial image signatures to the vehicle sensed information signatures (Fig. 5 and corresponding paragraphs).
Regarding claim 6, Shi teaches further comprising mapping the downloaded batch of aerial image signatures to the vehicle sensed information signatures. (Fig. 5 and corresponding paragraphs, e.g. Feature Extracting).
Regarding claim 9, Shi teaches wherein the downloading is further based on a geographic indication(Satellite images 403 include location data in global coordinates that can be used to determine the location in global coordinates of any point in the satellite image 403, Fig. 5 and corresponding paragraphs, selectively download images to include an estimated three DoF pose 302).
Regarding claim 21, Shi does not explicitly teach but Basalamah teaches wherein the duration between one point in time to another when the autonomous vehicle is located within an urban environment exceeds the duration between one point to another when the autonomous vehicle is located within a rural region (Basalamah, [0028],[0040], [0055] ).
The same motivation to combine as the parent claim applies here.
Regarding claim 22, Shi does not explicitly teach but Basalamah teaches wherein the duration is further responsive to historical information about statistics of downloading of batches of aerial image signatures made at a current location of the autonomous vehicle (Basalamah, [0019][0037],[0099]The updating threshold is set in advance and can be predetermined for various locations based on the population, number of registered vehicles within a predefined geographic location and/or based on historical traffic information for the region).
Regarding claim 23, Shi does not explicitly teach but Basalamah teaches wherein the historical information is related to a human driver that currently drives the autonomous vehicle (Basalamah, [0019][0037],[0099]).
The same motivation to combine as the parent claim applies here.
Regarding claim 24, Shi does not explicitly teach but Basalamah teaches wherein the historical information is related to a group of drivers driving a group of vehicles(Basalamah, [0019][0037],[0099]) .
The same motivation to combine as the parent claim applies here.
Regarding claim 25, Shi does not explicitly teach but Basalamah teaches wherein the duration is further responsive to historical information about statistics of downloading of batches of aerial image signatures made at a current location of the autonomous vehicle and at other locations withing one or more other locations that are of a same type as the environment as the environment in which the autonomous vehicle is located during the driving session (Basalamah, [0019][0037],[0099]).
The same motivation to combine as the parent claim applies here.
Regarding claim 26, Shi does not explicitly teach but Basalamah teaches wherein the type is selected of a dense urban environment, a city center, a suburban region, an industrial zone or a rural area (Basalamah, [0019][0037],[0099], [0028], [0055], [0079]).
The same motivation to combine as the parent claim applies here.
Regarding claim 28, Shi does not explicitly teach but Basalamah teaches wherein the duration is further based on an availability of a resource of the autonomous vehicle used in the downloading or the processing of one or more aerial image signatures, wherein the method further comprises determining the availability of the resource by probing the resource and performing, by the controller, a statistical analysis regarding the usage of any of resource over time ([0099] The data collected by the monitors 108 is sent using any communication interface to the backend server 102 to be processes and analyzed. Using stored historical data and statistical inferences; it is possible to estimate the crowd and transportation densities).
The same motivation to combine as the parent claim applies here.
Claims 2, 7-8 and 27 are rejected under 35 U.S.C. 103 as being obvious over Shi (US 20250095169 A1) in view of Basalamah (US 20160078756 A1) in view of Dotan (US 20060025923 A1)
Regarding claim 2, Shi ([0038]) teaches high-definition maps typically require extensive mapping efforts and large amounts of computer resources to produce and store the HD maps, along with large amounts of network bandwidth typically consumed to download the HD maps to vehicles 110, not to mention the large amount of computer memory typically required to store the maps in computing devices 115 included in vehicles. Shi as modified by Basalamah does not explicitly teach but Dotan teaches wherein the determining is based on, at least in part, an indicator of aerial image signatures download status ([0105] the server downloads the map data gradually, in order not to overload the limited memory capacity of the client device and to use the available wireless bandwidth efficiently. [0121] if the memory of the client device is insufficient to hold the entire corridor map, or if bandwidth constraints make continuous streaming impractical, the server may download the map data in pieces, in response to the location of the vehicle along the route).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, matching a ground view image and an aerial view image, as taught by Shi as modified by Basalamah, dynamically determining one or more downloading parameters of a downloading of a batch of aerial image signatures, as taught by Dotan, as Shi, Basalamah and Dotan are directed to downloading images to vehicles (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using dynamically determining one or more downloading parameters of a downloading of a batch of aerial image signatures and predictably applied it to Shi as modified by Basalamah’s teaching to solve the limited resource e.g. network bandwidth and storage.
Regarding claim 7, Shi as modified by Basalamah does not explicitly teach but Dotan teaches wherein the downloading is further based on an availability of out-of-vehicle communication resources ([0105] the server downloads the map data gradually, in order not to overload the limited memory capacity of the client device and to use the available wireless bandwidth efficiently. [0121] if the memory of the client device is insufficient to hold the entire corridor map, or if bandwidth constraints make continuous streaming impractical, the server may download the map data in pieces, in response to the location of the vehicle along the route).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, matching a ground view image and an aerial view image, as taught by Shi as modified by Basalamah, dynamically determining one or more downloading parameters of a downloading of a batch of aerial image signatures, as taught by Dotan, as Shi, Basalamah and Dotan are directed to downloading images to vehicles (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using dynamically determining one or more downloading parameters of a downloading of a batch of aerial image signatures and predictably applied it to Shi as modified by Basalamah’s teaching to solve the limited resource e.g. network bandwidth and storage.
Regarding claim 8, Shi as modified by Basalamah does not explicitly teach but Dotan teaches wherein the downloading is further based on a data traffic indication ([0105] the server downloads the map data gradually, in order not to overload the limited memory capacity of the client device and to use the available wireless bandwidth efficiently. [0121] if the memory of the client device is insufficient to hold the entire corridor map, or if bandwidth constraints make continuous streaming impractical, the server may download the map data in pieces, in response to the location of the vehicle along the route).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, matching a ground view image and an aerial view image, as taught by Shi as modified by Basalamah, dynamically determining one or more downloading parameters of a downloading of a batch of aerial image signatures, as taught by Dotan, as Shi, Basalamah and Dotan are directed to downloading images to vehicles (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using dynamically determining one or more downloading parameters of a downloading of a batch of aerial image signatures and predictably applied it to Shi as modified by Basalamah’s teaching to solve the limited resource e.g. network bandwidth and storage.
Regarding claim 27, Shi as modified by Basalamah does not explicitly teach but Basalamah teaches wherein the duration is further based on an availability of a resource of the autonomous vehicle used in the downloading or the processing of one or more aerial image signatures, wherein the method further comprises determining the availability by the resource ([0105] the server downloads the map data gradually, in order not to overload the limited memory capacity of the client device and to use the available wireless bandwidth efficiently. [0121] if the memory of the client device is insufficient to hold the entire corridor map, or if bandwidth constraints make continuous streaming impractical, the server may download the map data in pieces, in response to the location of the vehicle along the route ).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, matching a ground view image and an aerial view image, as taught by Shi as modified by Basalamah, dynamically determining one or more downloading parameters of a downloading of a batch of aerial image signatures, as taught by Dotan, as Shi, Basalamah and Dotan are directed to downloading images to vehicles (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using dynamically determining one or more downloading parameters of a downloading of a batch of aerial image signatures and predictably applied it to Shi as modified by Basalamah’s teaching to solve the limited resource e.g. network bandwidth and storage.
Claim 29 is rejected under 35 U.S.C. 103 as being obvious over Shi (US 2025/0095169 A1) in view of Basalamah (US20160078756 A1) in view of Christensen (US 10403133 B1)
Regarding claim 29, Shi as modified by Basalamah does not explicitly teach but Basalamah teaches wherein the duration is further based on an availability of a resource of the autonomous vehicle used in the downloading or the processing of one or more aerial image signatures, wherein the method further comprises determining the availability of the resource by evaluating one or more process or thread currently executed by the resource and deducting the availability of the resource based on the one or more process or thread currently executed by the resource( Christensen, additional processing and memory usage may be required to perform such vehicle operation, as a vehicle device may need to download additional data and process this data as part of the automatic autonomous vehicle operation).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, matching a ground view image and an aerial view image, as taught by Shi as modified by Basalamah, determining the availability of the resource by evaluating one or more process, as taught by Christensen, as Shi, Basalamah and Christensen are directed to downloading images to vehicles (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using determining the availability of the resource by evaluating one or more process and predictably applied it to Shi as modified by Basalamah’s teaching to solve the limited resource e.g. network bandwidth and storage.
Prior Art
Please refer to form 892 for cited references.
The prior art made of record on form PTO-892 and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
It is noted that any citation to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33,216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006,1009, 158 USPQ 275,277 (CCPA 1968)).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JINGLI WANG whose telephone number is (571)272-8040. The examiner can normally be reached on Mon-Fri 9 am-5 pm EST.
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/J.W./ Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/ Supervisory Patent Examiner, Art Unit 3666
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