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 judicial exception(s) without significantly more.
[STEP 1] The claim recites at least one step or structure. Thus, the claim is to a process or product, which is one of the statutory categories of invention (Step 1: YES).
[STEP2A PRONG I] The claim(s) 1, 7 and 13 recite(s):
A computer-implemented method for driver training using zone of proximal learning (ZPL), the method comprising:
receiving, by one or more processors, driving data with respect to a driver operating a vehicle;
estimating, using a personal behavior model, a driver profile based on the driving data;
estimating one or more zone of proximal development (ZPD) states based at least in part on the driver profile; and
performing one or more vehicle actions to place the driver into the one or more ZPD states1.
7. A system for driver training using zone of proximal learning (ZPL), the system comprising:
one or more processors;
a non-transitory, computer-readable medium storing instructions that, when executed by the one or more processors, cause the one or more processors to:
receive driving data with respect to a driver operating a vehicle;
estimate, using a personal behavior model, a driver profile based on the driving data;
estimate one or more zone of proximal development (ZPD) states based at least in part on the driver profile; and
generate commands to perform one or more vehicle actions to place the driver into the one or more ZPD states.
13. A Vehicle comprising:
one or more sensors operable to generate driving data with respect to a driver operating the vehicle;
one or more processors;
a non-transitory, computer-readable medium storing instructions that, when executed by the one or more processors, cause the one or more processors to:
receive the driving data;
estimate, using a personal behavior model, a driver profile based on the driving data;
estimate one or more zone of proximal development (ZPD) states based at least in part on the driver profile; and
generate commands to perform one or more vehicle actions to place the driver into the one or more ZPD states.
The non-highlighted aforementioned limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation between people but for the recitation of generic computer components. That is, other than reciting “sensors”, “processors”, “a non-transitory, computer-readable medium”, “vehicle”, nothing in the claim element precludes the step from practically being performed between people. For example, but for the recited language, the step in the context of this claim encompasses an instructor observing the user’s driving behavior, estimating the user’s driving need to improve their driving skill and providing instruction to improve the user’s driving skill. If a claim limitation, under its broadest reasonable interpretation, covers managing interactions between people, then it falls within the “Organization of Human Activity” or “Mental Process” grouping of abstract ideas.
Accordingly, the claim recites a judicial exception, and the analysis must therefore proceed to Step 2A Prong Two.
[STEP2A PRONG II] This judicial exception is not integrated into a practical application. In particular, the claim only recites the additional element(s) – “sensors”, “processors”, “a non-transitory, computer-readable medium”, “vehicle”.
The “sensors”, “processors”, “a non-transitory, computer-readable medium”, “vehicle” in the aforementioned steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component or are merely directed to a filed of used or technological environment.
Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. (Step 2A: YES).
[STEP2B] The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the aforementioned steps amounts to no more than mere instructions to apply the exception using a generic computer component, which cannot provide an inventive concept (for example, see paragraph 34 using general purpose computer) and directed to a field of used or technological environment.
As noted previously, the claim as a whole merely describes how to generally “apply” the aforementioned concept in a computer environment. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
The claim is not patent eligible. (Step 2B: NO).
Claim(s) 2-6, 8-12, 14-20 are dependent on supra claim(s) and includes all the limitations of the claim(s). Therefore, the dependent claim(s) recite(s) the same abstract idea. For example, claims 2-3, 8-9 and 14-15 are directed to abstract idea of determining rewards when the user performs within set of scenarios; claims 4, 10, 16 are directed to the abstract idea of providing instruction that the user received to improve their driving behavior; claims 6, 12 and 18 are directed to the abstract idea of performing cyclical improvement and observation to be used to improve the system; claims 19 and 20 are directed to data gathering steps (insignificant extra-solution activity). Claims 5, 11 and 17 appears to be the claims most likely that could overcome the current rejection. However, specifications paragraph 26 states that autonomous vehicle action may include informing the driver that he/she may need to take control of the vehicle (abstract idea). The claim recites no additional limitations. Accordingly, the additional element(s) do(es) not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea and the claim is therefore directed to the judicial exception. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Thus, even when viewed as a whole, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 120 as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Application No. 63/589,506, fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application:
Independent claims 1, 7 and 13 are claimed as computer implemented functional claims and as such require a disclosure of the computer and the algorithm (e.g., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor possessed the claimed subject matter at the time of filing. An algorithm is defined, for example, as “a finite sequence of steps for solving a logical or mathematical problem or performing a task.” Microsoft Computer Dictionary (5th ed., 2002). Applicant may “express that algorithm in any understandable terms including as a mathematical formula, in prose, or as a flow chart, or in any other manner that provides sufficient structure.” Finisar Corp. v. DirecTV Grp., Inc., 523 F.3d 1323, 1340, 86 USPQ2d 1609, 1623 (Fed. Cir. 2008) (internal citation omitted). It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See, e.g., Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683, 114 USPQ2d 1349, 1356, 1357 (Fed. Cir. 2015).
Independent claims 1, 7 and 13 require a disclosure of the limitation “estimate one or more zone of proximal development (ZPD) states based at least in part on the driver profile” and “generate commands to perform one or more vehicle actions to place the driver into the one or more ZPD states”. However, provisional application 63/589,506 fails to provide the necessary algorithm to perform the function of “estimate one or more zone of proximal development (ZPD) states based at least in part on the driver profile” and “generate commands to perform one or more vehicle actions to place the driver into the one or more ZPD states”.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1, 5-7, 11-13, 17-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Huang US 20100209889
Claim 1: The Huang reference provide a teaching of a computer-implemented method for driver training using zone of proximal learning (ZPL), the method comprising:
receiving, by one or more processors, driving data with respect to a driver operating a vehicle (see paragraph 65 driver controlling vehicle and detecting various sensor input and paragraph 209 examples of the use of steering wheel to detect the driver input );
estimating, using a personal behavior model, a driver profile based on the driving data (see paragraph 84 driver skill profile);
estimating one or more zone of proximal development (ZPD) states based at least in part on the driver profile (see paragraph 87); and
performing one or more vehicle actions to place the driver into the one or more ZPD states (see paragraph 242 corrective action based on the driver profile and sensed data).
Claims 5, 11 and 17: The Huang reference provides a teaching wherein the one or more vehicle actions comprises one or more autonomous vehicle controls (see paragraph 242 corrective action based on the driver profile and sensed data).
Claims 6, 12 and 18: The Huang reference provide a teaching wherein comprising continuously updating the ZPD states over time (see paragraph 459).
Claim 19: The Huang reference provide a teaching of wherein the driving data comprises one or more of vehicle data (see paragraph 156 vehicle data such as speed and vehicle manuever), environment data (see paragraph 119 camera lidar to detect environmental data), and driver behavior data (see paragraph 149 driver behavioral data).
Claim 20: The Huang reference provides a teaching of wherein the one or more sensors comprises a camera (see paragraph 77 camera for the front and rear of the vehicle).
Claim 7: The Huang reference provides a teaching of a system for driver training using zone of proximal learning (ZPL), the system comprising:
one or more processors (see paragraph 80 processor);
a non-transitory, computer-readable medium storing instructions that, when executed by the one or more processors, cause the one or more processors to:
receive driving data with respect to a driver operating a vehicle; estimate, using a personal behavior model, a driver profile based on the driving data (see paragraph 65 driver controlling vehicle and detecting various sensor input and paragraph 209 examples of the use of steering wheel to detect the driver input );
estimate one or more zone of proximal development (ZPD) states based at least in part on the driver profile (see paragraph 87); and
generate commands to perform one or more vehicle actions to place the driver into the one or more ZPD states (see paragraph 242 corrective action based on the driver profile and sensed data).
Claim 13: The Huang reference provide a teaching of a vehicle (see paragraph 77 vehicle 10) comprising:
one or more sensors operable to generate driving data with respect to a driver operating the vehicle (see paragraph 77, 79 camera and lidar);
one or more processors (see paragraph 80 processor);
a non-transitory, computer-readable medium storing instructions that, when executed by the one or more processors, cause the one or more processors to:
receive the driving data (see paragraph 65 driver controlling vehicle and detecting various sensor input and paragraph 209 examples of the use of steering wheel to detect the driver input );
estimate, using a personal behavior model, a driver profile based on the driving data (see paragraph 84 driver skill profile);
estimate one or more zone of proximal development (ZPD) states based at least in part on the driver profile (see paragraph 87); and
generate commands to perform one or more vehicle actions to place the driver into the one or more ZPD states (see paragraph 242 corrective action based on the driver profile and sensed data).
Claims 1, 7 and 13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Araki US 20240034335
Claim 1: The Araki reference provide a teaching of a computer-implemented method for driver training using zone of proximal learning (ZPL), the method comprising:
receiving, by one or more processors, driving data with respect to a driver operating a vehicle (see paragraph 52 collecting driver performance data based on the driver’s vehicle input);
estimating, using a personal behavior model, a driver profile based on the driving data (see paragraph 64 estimating the driver’s profile);
estimating one or more zone of proximal development (ZPD) states based at least in part on the driver profile (see paragraph 46); and
performing one or more vehicle actions to place the driver into the one or more ZPD states (see paragraph 63 providing autonomous vehicle action as part of the education/learning system).
Claim 7: The Araki reference provides a teaching of a system for driver training using zone of proximal learning (ZPL), the system comprising:
one or more processors (see paragraph 37 processor);
a non-transitory, computer-readable medium storing instructions that, when executed by the one or more processors, cause the one or more processors to:
receive driving data with respect to a driver operating a vehicle; estimate, using a personal behavior model, a driver profile based on the driving data (see paragraph 52 collecting driver performance data based on the driver’s vehicle input);
estimate one or more zone of proximal development (ZPD) states based at least in part on the driver profile (see paragraph 46); and
generate commands to perform one or more vehicle actions to place the driver into the one or more ZPD states (see paragraph 63 providing autonomous vehicle action as part of the education/learning system).
Claim 13: The Araki reference provide a teaching of a vehicle (see paragraph 33 vehicle 102) comprising:
one or more sensors operable to generate driving data with respect to a driver operating the vehicle (see paragraph 38);
one or more processors (see paragraph 37 processor);
a non-transitory, computer-readable medium storing instructions that, when executed by the one or more processors, cause the one or more processors to:
receive the driving data ((see paragraph 52 collecting driver performance data based on the driver’s vehicle input);
estimate, using a personal behavior model, a driver profile based on the driving data (see paragraph 64 estimating the driver’s profile);
estimate one or more zone of proximal development (ZPD) states based at least in part on the driver profile (see paragraph 46); and
generate commands to perform one or more vehicle actions to place the driver into the one or more ZPD states (see paragraph 63 providing autonomous vehicle action as part of the education/learning system).
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.
Claims 4, 10 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Huang US 20100209889 and in view of Armitage US 20140199662
Claims 4, 10 and 16: The Huang reference is silent on the teaching wherein the one or more vehicle actions comprises issuing an instruction to the driver.
However, the Armitage provides a teaching of wherein the one or more vehicle actions comprises issuing an instruction to the driver (see paragraph 27 “constructive feedback”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the with the feature of wherein the one or more vehicle actions comprises issuing an instruction to the driver, as taught by the Armitage reference, in order to better improve their driving ability.
Claims 2-3, 8-9 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Huang US 20100209889 and in view of Jarvis 20150019270
Claims 2 and 8: The Huang reference is silent on the teaching of generating, using a rewards estimator, rewards to the driver based on the driving data, wherein the one or more ZPD states are estimated based on the driver profile and the rewards.
However, the Jarvis reference provides a teaching of generating, using a rewards estimator, rewards to the driver based on the driving data, wherein the one or more ZPD states are estimated based on the driver profile and the rewards (see paragraph 66).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Huang reference with the feature of generating, using a rewards estimator, rewards to the driver based on the driving data, wherein the one or more ZPD states are estimated based on the driver profile and the rewards, as taught by the Jarvis reference, in order to help motivate the user improve their driving behavior (see paragraph 33).
Claims 3, 9 and 15: The Huang reference is silent on the teaching of wherein the rewards estimator is operable to generate one or more rewards when the driving data is indicative of satisfying one or more ZPD states.
However, the Jarvis reference provides a teaching of wherein the rewards estimator is operable to generate one or more rewards when the driving data is indicative of satisfying one or more ZPD states (see paragraph see paragraph 58).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Huang reference with the feature of wherein the rewards estimator is operable to generate one or more rewards when the driving data is indicative of satisfying one or more ZPD states, as taught by the Jarvis reference, in order to help motivate the user improve their driving behavior (see paragraph 33).
Claim 14: The Huang reference is silent on the teaching wherein the instruction further cause the one or more processor to generate using a reward estimator, rewards to the driver based on their driving data; and the one or more ZPD states are estimated based on the driver profile and the rewards.
However, the Jarvis reference wherein the instruction further cause the one or more processor to generate using a reward estimator, rewards to the driver based on their driving data (see paragraph 66); and the one or more ZPD states are estimated based on the driver profile and the rewards (see paragraph 75-76).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the Huang reference with the feature of wherein the instruction further cause the one or more processor to generate using a reward estimator, rewards to the driver based on their driving data; and the one or more ZPD states are estimated based on the driver profile and the rewards, as taught by the Jarvis reference, in order to help motivate the user improve their driving behavior (see paragraph 33).
Response to Arguments
Applicant's arguments filed 08/14/2026 have been fully considered but they are not persuasive.
With respect to applicant’s argument that the examiner has applied heightened standard of written description under 35 U.S.C 112(f) when determining if the provisional application 63/589,506. The applicant respectfully disagrees. MPEP 2161.01 cited in the rejection rationale are directed to all computer implemented invention. Furthermore, MPEP 2161.01 provide an explicit requirement that:
“Even if a claim is not construed as a means-plus- function limitation under 35 U.S.C. 112(f), computer-implemented functional claim language must still be evaluated for sufficient disclosure under the written description and enablement requirements of 35 U.S.C. 112(a).”
As such, the examiner takes the position the current rejection rationale under 35 U.S.C 112(a) written description requirement are still in effect.
The applicant also argued that paragraph 7, 10 and 13 from the provisional application 63/589,506 shows the necessary written description support for the limitations “estimate one or more zone of proximal development states based at least in part on the driver profile” and “generate commands to perform one or more vehicle action to place the driver into the one or more ZPD”. However, paragraphs 7, 10 and 13 do not provide the necessary algorithm necessary to achieve the function of “estimate one or more zone of proximal development states based at least in part on the driver profile” and “generate commands to perform one or more vehicle action to place the driver into the one or more ZPD”. Instead, these paragraphs only provide the results of the estimation and the command. Accordingly, the examiner maintains the finding that the provisional application 63/589,506 fails to provide written description support necessary to establish the benefit of early filing date. Accordingly, the Araki prior art are still considered to be valid prior art.
The Applicant argued that the Araki reference does not provide the teaching of “estimating one or more zone of proximal development (ZPD) states based at least in part on the driver profile" as recited by independent claim 1 and similarly recited by independent claims 7 and 13. The Applicant argued that the Araki infers a driver's current skill level and emotional state and selects a curriculum level and difficulty level commensurate with the driver's current abilities and matching a difficulty tier to a driver's assessed skill is not estimating a ZPD state. Instead, the Applicant argued A ZPD state identifies tasks beyond the driver's current independent capability but within reach with guidance. The examiner notes that the applicant’s argument is not commensurate with the current claim limitation of claim 1, 7 and 13. The Examiner proposes that the applicant would amend limitation related to the ZPD to include explicit limitations that necessitate such interpretation.
The Applicant also argued that the Araki does not provide “performing one more vehicle action to place the driver into the one or more ZPD states”. The Applicant argued that this limitation should be interpreted as an autonomous vehicle action performed by the vehicle. The examiner respectfully disagrees since this interpretation is not in line with Applicant specification. Paragraph 25 of the Applicant’s specification that the vehicle action may include “… the vehicle actions 154 may include transmitting instructions to a driving instructor that is teaching the driver how to drive. For example, the instructions may be transmitted to a computing device operated by the driving instructor. The driving instructor may then verbally relay the instructions to the driver. Embodiments are not limited by any particular instructions. As non-limiting examples, the instructions may be “Please speed up to the speed limit,” “Please turn left and then drive through the round-a-bout,” and “Exit the highway at the next exit.” The instructions may also include recommendations and suggestions to the driver, such as, without limitation, “Slow down when going into the upcoming curve,” “Keep checking your rearview mirror,” and “Remember to stop at the correct location at the stop sign.” Since the Applicant’s own specification allows for the “vehicle action” to include instruction to the user, the current rejection rationale will still be applied.
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 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.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROBERT J UTAMA whose telephone number is (571)272-1676. The examiner can normally be reached 9:00 - 17:30 Monday - Friday.
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, Kang Hu can be reached at (571)270-1344. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ROBERT J UTAMA/Primary Examiner, Art Unit 3715
1 Paragraph 25 states that vehicle action may include providing transmitting instructions from a driving instructor that is teaching the driver how to drive.
