DETAILED ACTION
Responsive to the Applicant reply filed on 11/04/2025, Applicant's amendments to claims have been entered and respective arguments carefully considered and responded in following:
On this Office Action, claims 1-20, consisting of independent claims 1, 9 and 17.
Claims 1-20 are pending.
Claims 1-2, 8-10 and 16-18 are rejected under the 35 USC § 103.
Claims 3-7, 11-15 and 19-20 are objected to as being dependent upon a rejected base claims.
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 Amendment
The amendment filed 11/04/2025 has been entered.
Claims 1, 3-5, 7, 12, 19 and 20 have been amended.
Response to Arguments
As per Claim Objections
Applicant’s arguments with respect to Claim Objections have been fully considered and are persuasive. The Claim Objections has been withdrawn.
As per Claim Rejections - 35 USC § 103
Applicant's arguments filed 11/04/2025 have been fully considered but they are not persuasive.
Applicant submits that Hong fails to teach or suggest: A) anonymized mobility data, B) a map tile having an anonymized trajectory, and C) whether the anonymized mobility data is satisfactory, as set forth in the arguments reproduced below.
With respect to the arguments on pages 11-12, in response to the argument below:
“Applicant further submits that Hong's own disclosure includes an understanding of map tiles, reciting in paragraph [0044] "In some instances, the map can be stored in a tiled format, such that individual tiles of the map represent a discrete portion of an environment, and can be loaded into working memory as needed, as discussed herein." This disclosure is commensurate with the map tiles as disclosed by the present application. However, the described map tiles of Hong are not used for any portion of the process described with respect to heat maps. Thus, it is evident that Hong cannot reasonably be interpreted to teach or suggest the determination of a map tile where anonymization of a trajectory using a first anonymization level fails to satisfy a predetermined anonymity parameter value.”
The examiner disagrees with the applicant’s argument because, as acknowledged by the applicant, Hong disclose the map tile in the form of the one or more maps 228 in paragraph [0044], and further discloses that “The image generation component 232 can receive data about the environment itself from … , and the one or more maps 228” in paragraph [0048] and further discloses that “the heat map generation component 234, can include functionality to receive the image(s) generated by the image generation component 232” in paragraph [0052]. Furthermore, Hong discloses that the heat map includes a tiled format through stating that ““the heat map generation component 234 can represent a discretized region of the environment proximate to the autonomous vehicle. For example, the heat map can represent a 64×64 grid (or J×K sized grid) representing a 100 meter by 100 meter region” and “the heat map can represent any size of region and can represent any number of discrete portions of the region” in paragraph 0054. For example, Examples 328, 330, and 332 illustrating the heat maps 136, 138, and 140, respectively, in Figure 3 may be considered as the claimed map tiles. For this reason, the examiner determines that Hong is reasonably interpreted to teach or suggest the determination of a map tile. Therefore, the argument is unpersuasive.
With respect to the arguments on page 12, in response to the argument below:
“Applicant further submits that Hong fails to teach or suggest to "remove a subset of the anonymized mobility data corresponding to the one or more map tiles" as Hong describes only a process of masking prediction probabilities on a heat map, which again fails to relate to the map tiles Hong describes and instead only relates to heat maps which are generated based on an image input to a prediction system as described in paragraph [0031]. Even then, Hong does not remove data based on the heat map, but instead masks a portion of data within the heat map.”
As responded above, the examiner determined that Hong discloses discrete portions (or J×K sized grid) of the region in the heat map. Additionally, Hong discloses, in paragraph [0054], that a portion of the heat map can be referred to as a cell of the heat map. Each cell can comprise a prediction probability representing a probability that the agent will be at the corresponding location in the environment at the time corresponding to the heat map. For this reason, a cell of the heat map disclosed by Hong may be considered as the map tile as claimed.
Additionally, as explained in paragraphs [0091]-[0098], masked portions of the prediction probabilities associated with each heat map that are under a threshold value have been removed, and the predicted trajectories are then output at operation 342. Therefore, the argument is unpersuasive.
With respect to the arguments on page 12-13, in response to the argument below:
“The Office Action cites to paragraph [0061] of Balu as disclosing the aforementioned claim feature and suggesting that the "partition-based clustering technique" of Balu corresponds with the plurality of map tiles of Claim 1. This interpretation is flawed, as the "partitions" of Balu are created based on a clustering technique associated with the trajectory data and unrelated to the underlying map data. Conversely, as recited in Claim 1, anonymized mobility data is
received "for a geographic region subdivided into a plurality of map tiles," where these map tiles are defined sub-sections of a map geometry as described in paragraph [0068] and similarly understood in the disclosure of Hong. …. Balu does not divide a map with partitions, but instead bases partitions on the trajectory data. … Applicant submits that these partitions are distinct from the claimed "plurality of map tiles" into which a geographic region is subdivided" and that these partitions are clearly distinct from the "tiles" recited in Hong. Thus, Applicant asserts that Balu fails to correct the admitted deficiencies of Hong, and the cited art, taken alone or in combination, fails to teach or suggest the features of the claims.”
The examiner disagrees with the applicant’s argument because, under the broadest reasonable interpretation, the limitation may be interpreted to encompass either the “map tiles” are pre-existing subdivisions of a map geometry, or instead partitions created based on the data is self. It is noted that the features upon which applicant relies (i.e., features defined in paragraph [0068]) are not recited in the rejected claims. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
As set forth in the motivation on pages 5-6 of the previous Non-final OC provided, the probe data, which is anonymized, includes a geographic location such as a longitude value, latitude value, height or altitude. This anonymized probe data is received for creating a geographic region subdivided into a plurality of map tiles.
Additionally, Balu further discloses “The probe data, or sampled points 51, are illustrated in an arrangement that is geographically spaced” and “The sampled points 51 form trajectory data. The coordinates may be measured on a local grid for the geographic region” in paragraphs [0061]-[0062]. Such a local grid may reasonably be considered as the claimed map tiles. Furthermore, the present application states in paragraph [0068] that “FIG. 3 illustrates an example embodiment of a map 300 of a geographic region that is subdivided into map tiles with gridlines 310. The segmentation of the geographic region can be performed according to any method of subdivision and is not limited to a square grid or to a tessellation.” For these reason, the argument is unpersuasive.
Therefore, the examiner respectfully disagrees with the arguments, and the rejection is maintained.
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.
Claims 1-2, 8-10 and 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Hong et al. (US 20200110416 A1, hereinafter “Hong”) in view of Balu (US 20200019815 A1).
Regarding independent claim 1, Hong discloses an apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and computer program code configured to, with the processor, cause the apparatus to at least (Hong: [0039] The vehicle computing device 204 can include one or more processors 216 and memory 218 communicatively coupled with the one or more processors 216):
determine, based on the anonymized mobility data, one or more map tiles of the plurality of map tiles where anonymization of the trajectories using the first anonymization level fails to satisfy a predetermined anonymity parameter value (Hong: [0044] the map can be stored in a tiled format, such that individual tiles of the map represent a discrete portion of an environment, and can be loaded into working memory as needed, as discussed herein; [0048] The image generation component 232 can receive data about agents in the environment from the perception component 222 … , and the one or more maps 228; [0052] the heat map generation component 234, can include functionality to receive the image(s) generated by the image generation component 232 (“one or more map tiles of the plurality of map tiles” See a specific example such as the grid provided in para.[0015]); [0091 and 0093] At operation 326, the process can include masking region(s) associated with a predicted trajectory. The operation 326 can generate masked heat maps corresponding to the heat maps 136, 138, and 140, respectively; [0094] At operation 340, the process can include determining whether prediction probabilities are under a threshold value (“first anonymization level fails to satisfy a predetermined anonymity parameter value”). For example, the operation 340 can include determining whether the unmasked portions of the prediction probabilities associated with each heat map are under a threshold value. If “no,” (indicating there are prediction probabilities that meet or exceed the threshold value), the process can return to the operation 304 to determine one or more predicted points based on the masked heat maps (“determine, one or more map tiles where anonymization of the trajectories”), which in turn can be used to determine additional predicted trajectories);
remove a subset of the anonymized mobility data corresponding to the one or more map tiles (Hong: [0091 and 0093-0095] At operation 326, the process can include masking region(s) associated with a predicted trajectory. The operation 326 can generate masked heat maps corresponding to the heat maps 136, 138, and 140, respectively (“remove a subset of the anonymized mobility data”). At operation 340, the process can include determining whether prediction probabilities are under a threshold value. The operation 340 can include determining whether the unmasked portions of the prediction probabilities associated with each heat map are under a threshold value. The process can return to the operation 304 to determine one or more predicted points based on the masked heat maps, which in turn can be used to determine additional predicted trajectories (another example of “remove a subset of the anonymized mobility data”); [0098] At operation 342, the process can include outputting predicted trajectory(ies) to a planning system to generate trajectory(ies) to control an autonomous vehicle (“a subset of the anonymized mobility data is removed”)); and
publish the anonymized mobility data without the subset of the anonymized mobility data corresponding to the one or more map tiles for use with one or more location-based services (Hong: [0095] For example, because the candidate point 316 was not masked by the mask 338 in the example 332, such a predicted point could be used to determine an additional predicted trajectory (“the anonymized mobility data without the subset of the anonymized mobility data”). … [0098] At operation 342, the process can include outputting predicted trajectory(ies) to a planning system to generate trajectory(ies) to control an autonomous vehicle. An example 344 illustrates the predicted trajectory 324 (e.g., based at least in part on the predicted points 312, 314, and 318) and a predicted trajectory 346 (e.g., based at least in part on the candidate point 316, which may have been determined to be a predicted point for the predicted trajectory 346)).
Hong discloses “the heat map can represent any size of region and can represent any number of discrete portions of the region” in paragraph 0015, “the map can be stored in a tiled format, such that individual tiles of the map represent a discrete portion of an environment” in paragraph 0044, and “At operation 326, the process can include masking region(s) associated with a predicted trajectory” in paragraph 0091. However, Hong does not disclose “receive anonymized mobility data for a geographic region subdivided into a plurality of map tiles, wherein the anonymized mobility data comprises a plurality of probe data points anonymized with a first anonymization level, wherein sequences of probe data points define trajectories.”
In a same field of endeavor, Balu teaches the apparatus, receive anonymized mobility data for a geographic region subdivided into a plurality of map tiles, wherein the anonymized mobility data comprises a plurality of probe data points anonymized with a first anonymization level, wherein sequences of probe data points define trajectories (Balu: [0061] The probe data includes trajectories as sequences of measurements of the probes; [0061] FIG. 5 illustrates an example trajectory data for a partition-based clustering technique (“a plurality of map tiles”) in order to find an optimal quantization of trajectory points to solve k-anonymization. In act S101, the anonymity controller 121 receives probe data from one or more probes 101 a-n or the database 123; [0062] The coordinates may be measured on a local grid (“a plurality of map tiles”) for the geographic region; after steps S103-S121, [0091] In act S125, the anonymity controller 121 is configured to output anonymized trajectory data (“receive anonymized mobility data”). The anonymity controller 121 may modify the trajectory data to provide the predetermined level of anonymity to locations from the trajectory data in response to the merged cluster).
Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified the elements disclosed by Hong with the teachings of Balu to receive anonymized mobility data for a geographic region subdivided into a plurality of map tiles, wherein the anonymized mobility data comprises a plurality of probe data points anonymized with a first anonymization level, wherein sequences of probe data points define trajectories. One of ordinary skill in the art would have been motivated to make this modification because the probe data may include a geographic location such as a longitude value and a latitude value. In addition, the probe data may include a height or altitude. The probe data may be collected over time and include timestamps (para. [0045]). Therefore, using probe data for defining trajectories may offer significant advantages for defining trajectories in the context of transportation analysis and management. In addition, , by using anonymity in geographic data, users of navigation, autonomous driving, assisted driving, traffic applications, and other location-based systems are more willing to adopt these systems given the technological advances in the data security (para. [0041]).
Regarding claim 2, the combination of Hong and Balu discloses all elements of the current invention as stated above. Balu teaches the apparatus of claim 1, wherein the anonymized mobility data for the geographic region comprises anonymized mobility data satisfying a minimum speed and map-matched to road segments within the plurality of map tiles (Balu: [0094] The traffic information such as the real time average speeds on or more road segments may be determined from the anonymized data 40; [0166] The geographic database 123 may also include other attributes of or about the roads such as, for example, geographic coordinates, street names, address ranges, speed limits, turn restrictions at intersections, and/or other navigation related attributes).
Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified the elements disclosed by Hong with the teachings of Balu to include anonymized mobility data satisfying a minimum speed and map-matched to road segments within the plurality of map tiles. One of ordinary skill in the art would have been motivated to make this modification because the road segment data and the node data indicate the location of the roads and intersections as well as various attributes of the roads and intersections (para.[0183]). Therefore, receiving the segments can be readily incorporated into the trajectory definition. In addition, by using anonymity in geographic data, users of navigation, autonomous driving, assisted driving, traffic applications, and other location-based systems, are more willing to adopt these systems given the technological advances in the data security (para. [0041]).
Regarding claim 8, the combination of Hong, Balu and Young teaches all elements of the current invention as stated above. Hong discloses the apparatus of claim 1, wherein the apparatus is further caused to:
apply a second anonymization level to the anonymized mobility data of the one or more map tiles of the plurality of map tiles where the anonymization of the trajectories using the first anonymization level fails to satisfy the predetermined anonymity parameter value to generate re-anonymized mobility data for the one or more map tiles (Hong: [0094] the process can include determining whether prediction probabilities are under a threshold value. For example, the operation 340 can include determining whether the unmasked portions of the prediction probabilities associated with each heat map are under a threshold value. If “no,” (indicating there are prediction probabilities that meet or exceed the threshold value), the process can return to the operation 304 (“apply a second anonymization level”) to determine one or more predicted points based on the masked heat maps, which in turn can be used to determine additional predicted trajectories);
determine if the re-anonymized mobility data satisfies the predetermined anonymity parameter value (Hong: [0094] If “no,” (indicating there are prediction probabilities that meet or exceed the threshold value) (“a second anonymization level”), the process can return to the operation 304 to determine one or more predicted points based on the masked heat maps, which in turn can be used to determine additional predicted trajectories); and
publish the re-anonymized mobility data for the one or more map tiles for use with the one or more location-based services in response to the re- anonymized mobility data satisfying the predetermined anonymity parameter value (Hong: [0097-0098] after the “no” determination, when there are no prediction probabilities under the threshold (e.g., “yes” in the operation 340), the process can continue to operation 342. At operation 342, the process can include outputting predicted trajectory(ies) to a planning system to generate trajectory(ies) to control an autonomous vehicle).
Regarding independent claims 9 and 17, they are a non-transitory readable storage medium having a plurality of computer executable instructions and a method that respectively corresponds to claim 1. Therefore, the claims are rejected for at least the same reasons as the apparatus of claim 1.
Regarding claims 10 and 18, they are a non-transitory readable storage medium having a plurality of computer executable instructions and a method that respectively corresponds to claim 2. Therefore, the claims are rejected for at least the same reasons as the apparatus of claim 2.
Regarding claim 16, it is a non-transitory readable storage medium having a plurality of computer executable instructions claim that corresponds to claim 8. Therefore, the claim is rejected for at least the same reasons as the apparatus of claim 8.
Allowable Subject Matter
Claims 3-7, 11-15 and 19-20 are objected to as being dependent upon a rejected base claims, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mayor et al. (US 11943679 B2): Col.8 LN.43-58, The map information received in step 403 may include map tiles, or other similar formats of map data files or structures, which include sets of geographic coordinates identifying the physical objects within the region covered by the map tile. For example, a map tile covering a particular region may include coordinate data that defines the precise size, shape, and boundaries for all streets, paths, buildings, natural or man-made landmarks, and other any fixed objects within the region. In addition to geographic coordinates, map tiles also may contain data identifying each unique object and its type (e.g., street, path, building, bodies of water, other natural landmarks, etc.), object names or labeling data, and other object properties. The map tiles or other map information received in step 403 may include any and all data needed by a map/navigation application 210 to render a map graphical user interface of the region.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW SUH whose telephone number is (571)270-5524. The examiner can normally be reached 9:00 AM- 5:00 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Carl Colin can be reached at (571) 272-3862. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ANDREW SUH/Examiner, Art Unit 2493