Prosecution Insights
Last updated: April 19, 2026
Application No. 18/960,058

DISTANCE PREDICTION METHOD, MODEL TRAINING METHOD, PLANNING-CONTROL SYSTEM AND RELATED APPARATUSES

Non-Final OA §101§103
Filed
Nov 26, 2024
Examiner
DEL VALLE, LUIS GERARDO
Art Unit
3666
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Momenta (Suzhou) Technology Co. Ltd.
OA Round
1 (Non-Final)
72%
Grant Probability
Favorable
1-2
OA Rounds
2y 11m
To Grant
96%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allow Rate
111 granted / 154 resolved
+20.1% vs TC avg
Strong +24% interview lift
Without
With
+23.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
30 currently pending
Career history
184
Total Applications
across all art units

Statute-Specific Performance

§101
13.1%
-26.9% vs TC avg
§103
60.5%
+20.5% vs TC avg
§102
11.2%
-28.8% vs TC avg
§112
12.7%
-27.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 154 resolved cases

Office Action

§101 §103
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 . Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Analysis of Claim 10: STEP 1: Does claim 1 fall within one of the statutory categories? Yes. The claim is directed toward an apparatus which falls within one of the statutory categories. STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? Yes, the claim is directed to an abstract idea. Claim 10. A distance prediction apparatus, wherein the apparatus comprises: one or more processors; the processors are coupled with a storage apparatus, the storage apparatus is used for storing one or more programs; when the one or more programs are executed by the one or more processors, the distance prediction apparatus is caused to: acquire a first global pose, a first expanded navigation path and first landmark information of a first vehicle, wherein the first global pose is a global pose of the first vehicle at a current moment, the first expanded navigation path comprises an expanded path of a first vehicle navigation path determined based on the first global pose, and the first landmark information comprises landmark information comprised in a first road environment image collected by the first vehicle at the first global pose; process the first global pose, the first expanded navigation path and the first landmark information based on a distance prediction model to obtain a farthest reachable distance on each lane in the first landmark information; acquire a distance training sample set before the first global pose, the first expanded navigation path and the first landmark information are processed based on the distance prediction model, wherein each training sample in the distance training sample set comprises: a second expanded navigation path, second landmark information, a second global pose and a truth value of a farthest reachable distance, wherein the second expanded navigation path comprises an expanded path of a second vehicle navigation path, the second landmark information comprises landmark information comprised in a second road environment image collected by a second vehicle on the second expanded navigation path, the second global pose comprises a global pose of the second vehicle when collecting the second road environment image, and the truth value of the farthest reachable distance comprises a truth value of a farthest reachable distance of each lane in the second landmark information; perform training by using the distance training sample set to obtain the distance prediction model. The limitations bolded in claim 10 above are a mental process that can be practicably performed in the human mind and utilizing pen and paper and, therefore, an abstract idea. The limitations of claim 10 highlighted above merely consists of acquiring a first vehicle’s a location on a road and the current environment of the same. Then, the previous occurs for a second vehicle and its corresponding location on the road and respective environment. After which, the apparatus is trained using the sample set pertaining to the distance of the vehicle. Thus, the claim recites a mental process. STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? No, the claim does not recite additional elements that integrate the judicial exception into a practical application. Claim 10. A distance prediction apparatus, wherein the apparatus comprises: one or more processors; the processors are coupled with a storage apparatus, the storage apparatus is used for storing one or more programs; when the one or more programs are executed by the one or more processors, the distance prediction apparatus is caused to: acquire a first global pose, a first expanded navigation path and first landmark information of a first vehicle, wherein the first global pose is a global pose of the first vehicle at a current moment, the first expanded navigation path comprises an expanded path of a first vehicle navigation path determined based on the first global pose, and the first landmark information comprises landmark information comprised in a first road environment image collected by the first vehicle at the first global pose; process the first global pose, the first expanded navigation path and the first landmark information based on a distance prediction model to obtain a farthest reachable distance on each lane in the first landmark information; acquire a distance training sample set before the first global pose, the first expanded navigation path and the first landmark information are processed based on the distance prediction model, wherein each training sample in the distance training sample set comprises: a second expanded navigation path, second landmark information, a second global pose and a truth value of a farthest reachable distance, wherein the second expanded navigation path comprises an expanded path of a second vehicle navigation path, the second landmark information comprises landmark information comprised in a second road environment image collected by a second vehicle on the second expanded navigation path, the second global pose comprises a global pose of the second vehicle when collecting the second road environment image, and the truth value of the farthest reachable distance comprises a truth value of a farthest reachable distance of each lane in the second landmark information; perform training by using the distance training sample set to obtain the distance prediction model. Claim 10 does not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. The additional elements underlined above do not integrate the abstract idea into practical application. The distance prediction apparatus, processors, storage apparatus, and programs are recited at a high level of generality and amounts to mere data gathering, which is also a form of insignificant extra solution activity. STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claim does not recite additional elements that amount to significantly more than the judicial exception. Claim 10 does not recite any specific limitation or combination of limitations that are not well-understood, routine, conventional (WURC) activity in the field. Acquire, process, and perform are fundamental, i.e. WURC, activities performed by the vehicle in claim 10. Claims 1 and 8 has the corresponding limitations of Claim 10 and as such the analysis of Claims 1 and 8 also utilizes the same as Claim 10. Claims 1 and 8 recite the limitations similar to Claim 10 and as such are at a high level of generality and amounts to mere data gathering, which is also a form of insignificant extra solution activity. CONCLUSION Thus, since claim 10 is: (a) directed toward an abstract idea, (b) does not recite additional elements that integrate the judicial exception into a practical application, and (c) does not recite additional elements that amount to significantly more than the judicial exception, it is clear that claim 10 is directed towards non-statutory subject matter. Analysis of Claims 11-16 and 20 Dependent claims 11-16 and 20 further limit the abstract idea without integrating the abstract idea into practical application or adding significantly more. More specifically, the limitations of claims 11-16 and 20 are, under their broadest reasonable interpretation, limitations that can be performed in the human mind using a similar analysis as applied to claim 10 above. As such, claims 11-16 and 20 are rejected under 35 USC 101 as being drawn to an abstract idea without significantly more, and thus are ineligible. Analysis of Claims 2-7, 9, 17-19 Dependent claims 2-7, 9, 17-19 further limit the abstract idea without integrating the abstract idea into practical application or adding significantly more. More specifically, the limitations of claims 2-7, 9, 17-19 are, under their broadest reasonable interpretation, limitations that can be performed in the human mind using a similar analysis as applied to claim 1 and 8 above. As such, claims 2-7, 9, 17-19 are rejected under 35 USC 101 as being drawn to an abstract idea without significantly more, and thus are ineligible. 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. 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, 8, 10, 17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ting., US 20110282573 A1 (herein, Ting) and in view of Tseng US 20230169863 A1 (herein, Tseng). Regarding Claims 1, 8, and 10, Ting discloses a distance prediction apparatus (FIG. 1, #s 1 – GPS and 2 – Electronic Device), wherein the apparatus comprises: one or more processors (FIG. 1, #21 – processors); the processors are coupled with a storage apparatus (FIG. 1, #19 – storage unit), the storage apparatus is used for storing one or more programs (¶[0009] – “…The application of the route planning data compression algorithm compresses the route planning data into a less number of recording points. Because the amount of data to be stored is reduced,…”); when the one or more programs are executed by the one or more processors (¶[0031] – “…the processor 21 of the electronic device 2 for causing the processor 21 to start computation and to produce a route planning data…”), the distance prediction apparatus is caused to: process the first global pose, the first expanded navigation path and the first landmark information based on a distance prediction model to obtain a farthest reachable distance on each lane in the first landmark information (See above 112b and ¶[0032] – “…the compressed route planning data from the storage unit 13 in the RAM 16 temporarily, and then converts the geographic coordinate data of the current location and the compressed route panning data into a planar or 3D navigation map, and then drives the display unit 17 (LCD monitor or touch panel) to display the map, the direction of the route, and the time and distance required to reach to the destination….”); perform training by using the distance training sample set to obtain the distance prediction model (FIG. 4 illustrates the steps to train the model, ¶[0036]). Ting discloses, acquire a first global pose, a first expanded navigation path and first landmark information of a first vehicle (¶[0005] – “A GPS receives satellite signals from a number of artificial satellites to determine the current location (longitude, latitude, and altitude to within a few meters. Receivers calculate the precise time as well as position, which can be used as a reference for scientific experiments. GPS is intensively used in cars, boats and other transportation vehicles for positioning to assist traveling or navigation….”), wherein the first global pose is a global pose of the first vehicle at a current moment (¶[0005] – “…precise time…”), the first expanded navigation path comprises an expanded path of a first vehicle navigation path determined based on the first global pose (See above 112b, ¶[0006] – “…advanced cars are equipped with a global navigation satellite system (GNSS) as a standard equipment. An advanced global navigation satellite system (GNSS) provides 3D actual view simulation and different route planning modes…”), but does not disclose, the first landmark information comprises landmark information comprised in a first road environment image collected by the first vehicle at the first global pose. However, Tseng teaches, the first landmark information comprises landmark information comprised in a first road environment image collected by the first vehicle at the first global pose (FIG. 3, ¶[0013] – “…The fixed object A3 is shown in the aerial photo, and a coordinate set of the fixed object A3 can be derived from a coordinate system (e.g. googlemaps url_link) of the aerial photo database…” – i.e., the first vehicle collects the image in the environment of FIG. 3). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus as disclosed by Ting to include road environment images as taught by Teng. Doing so, provides additional information pertaining to the navigation path. With this additional information, the driver can make a more informed decision and thus increase the safety for the same while operating the vehicle. Modified Ting further teaches, acquire a distance training sample set before the first global pose (¶[0031] – “…a keyboard or computer mouse (not shown) to the input/output port 23 of the electronic device 2, and then use the input device to input the location data of the predetermined destination into the processor 21 of the electronic device 2 for causing the processor 21 to start computation and to produce a route planning data (containing, for example, multiple landmarks or the optimal travel route to the destination)…”), the first expanded navigation path and the first landmark information are processed based on the distance prediction model (FIG. 4 process flowchart) and a truth value (¶[0034] – “…the predetermined distance (T) is explained to have a length value when compared to the length of the recording distances (d, d1, d2, d3, d4 . . . dn)….”), wherein each training sample in the distance training sample set comprises: but does not teach, a second expanded navigation path, second landmark information, a second global pose and a truth value of a farthest reachable distance, wherein the second expanded navigation path comprises an expanded path of a second vehicle navigation path, the second landmark information comprises landmark information comprised in a second road environment image collected by a second vehicle on the second expanded navigation path, the second global pose comprises a global pose of the second vehicle when collecting the second road environment image, and the truth value of the farthest reachable distance comprises a truth value of a farthest reachable distance of each lane in the second landmark information. However, Tseng teaches, a second expanded navigation path (FIG. 2 illustrates a second navigation path), second landmark information (FIGS. 2-3 illustrate 2nd landmark information), a second global pose and a truth value of a farthest reachable distance (¶[0014] – “The image processor 120 records the first coordinate of the first end A31 and the second coordinate of the second end A32 at the first fix dot A33 and the second fix dot A34 in the aerial view respectively, calculates a first distance from the first end A31 to the second end A32 using the pixels of the aerial photo, and calculates a second distance from the moving dot A22 to one of the first fix dot A33 and the second fix dot A34 based on the first distance to obtain the second position coordinate of the second vehicle A2…”), wherein the second expanded navigation path comprises an expanded path of a second vehicle navigation path (See above 112b and FIGS. 2-3 illustrate 2nd vehicle path), the second landmark information comprises landmark information comprised in a second road environment image collected by a second vehicle (FIGS. 2-3, A2 – second vehicle and second road environment images of the second path) on the second expanded navigation path, the second global pose comprises a global pose of the second vehicle (FIGS. 2-3 illustrate the second global pose of the second vehicle) when collecting the second road environment image, and the truth value of the farthest reachable distance comprises a truth value of a farthest reachable distance of each lane in the second landmark information (FIG. 3 illustrates the farthest reachable distance of each lane). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus as disclosed by modified Ting to include the aforementioned limitations as taught by Tseng. Doing so, provides additional information pertaining to the navigation path. With this additional information, the driver can make a more informed decision and thus increase the safety for the same while operating the vehicle. Regarding Claim 17, modified Tseng further teaches, a training apparatus for a distance prediction model (FIG. 1, #19 – supplementary unit), wherein the apparatus comprises: one or more processors (¶[0055] – “… the supplementary unit 19 that is electrically connected to the CPU 11 …”); the processors are coupled with a storage apparatus (¶[0018] – “…and an input/output port 18 and a supplementary unit 19 respectively electrically connected with the CPU 11.”), the storage apparatus is used for storing one or more programs; when the one or more programs are executed by the one or more processors, the training apparatus is caused to implement the method according to claim 8 (¶[0006] – “…a large program capacity is necessary, complicating the computation procedure. Because much data storage capacity and a relatively higher operating power of central processing speed are necessary,…”). Regarding Claim 19, modified Tseng further teaches, a vehicle, wherein the vehicle comprises the apparatus according to claim 10 (¶[0005] – “vehicle”). Claim(s) 2 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Ting., US 20110282573 A1 (herein, Ting) in view of Tseng US 20230169863 A1 (herein, Tseng), and in further view of Poppen et al., US 20180010920 A1 (herein, Poppen). Regarding Claims 2 and 11, modified Tseng teaches, Regarding Claims 2 and 11, modified Tseng further teaches, wherein the distance prediction apparatus is further caused to: acquire a target vehicle navigation path and a target global pose of a target vehicle travelling on the target vehicle navigation path in a case (¶[0005] – “A GPS receives satellite signals from a number of artificial satellites to determine the current location (longitude, latitude, and altitude to within a few meters. Receivers calculate the precise time as well as position, which can be used as a reference for scientific experiments. GPS is intensively used in cars, boats and other transportation vehicles for positioning to assist traveling or navigation….”) that a target expanded navigation path comprises the first expanded navigation path ¶[0006] – “…advanced cars are equipped with a global navigation satellite system (GNSS) as a standard equipment. An advanced global navigation satellite system (GNSS) provides 3D actual view simulation and different route planning modes…”) and/or the second expanded navigation path, wherein, when the target expanded navigation path is the first expanded navigation path, the target vehicle navigation path is the first vehicle navigation path (¶[0031] – “…a keyboard or computer mouse (not shown) to the input/output port 23 of the electronic device 2, and then use the input device to input the location data of the predetermined destination into the processor 21 of the electronic device 2 for causing the processor 21 to start computation and to produce a route planning data (containing, for example, multiple landmarks or the optimal travel route to the destination)…”), the target vehicle is the first vehicle, and the target global pose is the first global pose; when the target expanded navigation path is the second expanded navigation path (Tseng, FIGS. 2-3 illustrate 2nd vehicle path), the target vehicle navigation path is the second vehicle navigation path, and the target global pose is the second global pose (Tseng, FIG. 3, ¶[0013] – “…The fixed object A3 is shown in the aerial photo, and a coordinate set of the fixed object A3 can be derived from a coordinate system (e.g. googlemaps url_link) of the aerial photo database…” – i.e., the first vehicle collects the image in the environment of FIG. 3) Examiner’s Note: The above limitations, per the Specification are the rephrasing of already claimed subject matter, e.g. target vehicle is the first vehicle, target global pose is equivalent to “first global pose” and so. As such, the Examiner cited according to Claim 10 limitation. Modified Tseng further teaches, the target global pose, target data (¶[0009] – “…route planning data…”), navigation events ([0002] – “…to a route planning method for navigation…”), but does not disclose, extract point of interest (POI) information corresponding to the target global pose from target data, wherein the target data comprises navigation events and/or a vehicle navigation map, the POI information comprises road attribute information related to predicting the farthest reachable distance, and the POI information corresponding to the target global pose comprises POI information within a preset distance range in front of the target global pose on the target vehicle navigation path; add the POI information to the target vehicle navigation path to obtain the target expanded navigation path. However, Poppen teaches, extract point of interest (POI) information corresponding to the target global pose from target data, wherein the target data comprises navigation events and/or a vehicle navigation map, the POI information comprises road attribute information related to predicting the farthest reachable distance, and the POI information corresponding to the target global pose comprises POI information within a preset distance range in front of the target global pose on the target vehicle navigation path (Claim 1 – “… one or more points of interest along the second road that the user has not previously visited; and causing, by the computing system,…”); add the POI information to the target vehicle navigation path to obtain the target expanded navigation path (Claim 19 – “… one or more points of interest along the second road that the user has not previously visited; and causing, by the computing system,…”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus as disclosed by modified Ting to include the aforementioned limitations as taught by Poppen. Doing so, provides additional information pertaining to the navigation path that includes a point of interest. With this additional information, the driver can make a more informed decision and thus increase the safety for the same while operating the vehicle. Regarding Claim 20, modified Ting teaches a program and processor but does not disclose, a non-transitory computer-readable storage medium on which a computer program is stored, wherein when the program is executed by a processor, the method according to claim 1 is implemented. However, Poppen teaches, non-transitory computer-readable storage medium on which a computer program is stored, wherein when the program is executed by a processor, the method according to claim 1 is implemented (Claim 10 – “A computer program product comprising a non-transitory computer readable storage medium having instructions encoded thereon that, when executed by one or more processors,”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the apparatus as disclosed by modified Ting to include the non-transitory computer-readable storage medium as taught by Poppen. Doing so, provides the requisite structure so as to execute the programs that provide the necessary navigation information to the driver so as to operate safely the vehicle. Allowable Subject Matter Claims 3-7, 9, 12-16, and 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to LUIS G DEL VALLE whose telephone number is (303)297-4313. The examiner can normally be reached Monday-Friday, 0730 - 1630 MST. 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, Anne Antonucci can be reached at (313) 446-6519. 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. /LUIS G DEL VALLE/Examiner, Art Unit 3666 /ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666
Read full office action

Prosecution Timeline

Nov 26, 2024
Application Filed
Mar 06, 2026
Non-Final Rejection — §101, §103 (current)

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Prosecution Projections

1-2
Expected OA Rounds
72%
Grant Probability
96%
With Interview (+23.8%)
2y 11m
Median Time to Grant
Low
PTA Risk
Based on 154 resolved cases by this examiner. Grant probability derived from career allow rate.

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