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 .
Drawings
The drawings filed on February 28, 2024 are accepted.
Information Disclosure Statement
3. The Information Disclosure Statements filed on September 18, 2025 have been considered. An initialed copy of the Form 1449 is enclosed herewith.
Response to arguments
4. Applicant notes in the restriction requirement document Group II only consists of claims 11-19, Applicants further assume this is a typographical error and that the intention was Group II includes claim 10. In response, the Examiner agrees with the Applicant’s arguments, the restriction requirement is withdrawn. Thus claims 1-20 are pending.
Claim Rejections - 35 USC § 101
5. 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.
6. Claims 1-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Subject Matter Eligibility Standard
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter.
Under step 1 of the analysis, claims 1-19 are directed to system claims. The claims fall under one of the four statutory classes of invention.
If the claims do fall within one of the statutory categories, they must then be determined whether the claims are directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea).
Step 2A, Prong One, the claimed invention is directed to an abstract idea without significantly more.
Representative claim 1 recites the abstract idea in non-bold and the additional elements in bold:
a communications interface configured to:
receive a desired budget for the optimized supply planning over a future period of time;
receive one or more shift constraints for the optimized supply planning;
at least one processor configured to:
determine expected demand for the future period of time based on historical demand data;
determine quality of service as a function of a number of vehicles for each of a plurality of time bins based on the expected demand; and
determine optimized shifts for the rideshare management system that maximizes the quality of service based on the function in each of the plurality of time bins, the one or more shift constraints, the desired budget or any combination thereof.
Similar limitations comprise the abstract ideas of Claim 10.
Regarding claims 1 and 10, the limitations of “receive”, and “determine”, are a process that, under its broadest reasonable interpretation, covers organizing human activity concepts, but for the recitation of generic computer components.
Claim 2 further recites assign drivers to each of the optimized shifts based on driver availability, driver preferences, labor rules, salaries, or any combination thereof.
Accordingly, the steps or functions of assign, involve generic computer functions and are similar to mental steps.
Claim 3 further recites wherein the budget is total cost for operation over the future period of time, number of hours for vehicles over the future period of time, or any combination thereof.
Claim 4 further recites wherein determining optimized shifts is further based one or more set of predetermined shifts for the optimal supply planning, one or more supply plan objectives or any combination thereof. Accordingly, the steps or functions of determining, involve generic computer functions and are similar to mental steps.
Claim 5 further recites wherein determining the quality of service is further based on machine learning. Accordingly, the steps or functions of determining, involve generic computer functions and are similar to mental steps.
Claim 6 further recites wherein determining the quality of service is further based on expected weather, expected time of day, or any combination thereof. Accordingly, the steps or functions of “determining”, involve generic computer functions and are similar to mental steps.
Claim 7 further recites wherein determining the quality of service is further based on met demand, on-time performance, time it takes to serve an on-demand ride, or any combination thereof. Accordingly, the steps or functions of determining, involve generic computer functions and are similar to mental steps.
Claim 8 further recites determining the optimized shifts further comprises: determining contribution that a shift at a start of the shift, end of a shift or around a break time during the shift or any combination thereof has on the number of available vehicles. Accordingly, the steps or functions of determining, involve generic computer functions and are similar to mental steps.
Claim 9 further recites wherein the contribution is a fractional contribution to the number of available vehicles.
Claim 11 further recites wherein determining optimized shifts is further based one or more set of predetermined shifts for the optimal supply planning, one or more supply plan objectives. Accordingly, the steps or functions of determining, involve generic computer functions and are similar to mental steps.
Claim 12 further recites assign drivers to each of the optimized shifts based on the determined optimized shifts. Accordingly, the steps or functions of assign, involve generic computer functions and are similar to mental steps.
Claim 13 further recites determine demand level for each of a plurality of time bins to create an expected demand for each time bin based on historical met demand;
determine a percentage of demand met as a function of vehicle supply for each of the plurality of time bins based on the historical met demand; and
create a target supply vector based on the function.
Accordingly, the steps or functions of “determine” and “create” involve generic computer functions and are similar to mental steps.
Claim 14 further recites wherein determining the demand level is based on machine learning. Accordingly, the steps or functions of “determining”, involve generic computer functions and are similar to mental steps.
Claim 15 further recites wherein the demand level for each of the plurality of time bins is further based on expected weather. Accordingly, the steps or functions of “determining”, involve generic computer functions and are similar to mental steps.
Claim 16 further recites wherein determining required supply for the future period of time is further based on number of bookings for a future period, expected number of passengers vs. expected number of bookings, weather prediction, or any combination thereof. Accordingly, the steps or functions of “determining”, involve generic computer functions and are similar to mental steps.
Claim 17 further recites wherein determining optimized shifts is further based on the target supply vector. Accordingly, the steps or functions of “determining”, involve generic computer functions and are similar to mental steps.
Claim 18 further recites determining contribution that a shift at a start of the shift, end of a shift or around a break time during the shift or any combination thereof has on a number of available vehicles. Accordingly, the steps or functions of “determining”, involve generic computer functions and are similar to mental steps.
Claim 19 further recites wherein the contribution is a fractional contribution to the number of available vehicles.
Regarding claims 2-9, and 11-19, the claim limitations are a further process that, under its broadest reasonable interpretation, covers organizing human activity concepts, but for the recitation of generic computer components
That is, other than reciting a computing device and an equipment device, the claim limitations merely cover commercial interactions, including business relations, thus falling within the "Certain Methods of Organizing Human Activity" grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
Under Step 2A Prong Two, the eligibility analysis evaluates whether the claims as a whole integrates the recited judicial exception into a practical application of the exception. This judicial exception is not integrated into a practical application. The claims include a communications interface and a processor (Claims 1 and 10). The communications interface and a processor in the steps are recited at a high-level of generality, such that they amount no more than mere instructions to apply the exception using a generic computer component. Accordingly, the additional elements dos not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As a result, the claims are directed to an abstract idea.
The claims do not include additional element that is 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 a communications interface and a processor amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
The dependent claims described above do not recite additional limitations that are sufficient to amount to significantly more than the abstract idea. A more detailed abstract idea remains an abstract idea.
Under step 2B of the analysis, the claims include, inter alia, a communications interface and a processor.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
There isn't any improvement to another technology or technical field, or the functioning of the computer itself. Moreover, individually, there are not any meaningful limitations beyond generally linking the abstract idea to a particular technological environment, i.e., implementation via a computer system. Further, taken as a combination, the limitations add nothing more than what is present when the limitations are considered individually. There is no indication that the combination provides any effect regarding the functioning of the computer or any improvement to another technology.
In addition, as discussed in Paragraphs 0163 and 0164 of the specification, " Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor receives instructions and data from a read-only memory or a random access memory or both. The essential elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Generally, a computer can be operatively coupled to receive data from and/or transfer data to one or more mass storage devices for storing data (e.g., magnetic, magneto-optical disks, or optical disks).
Data transmission and instructions can also occur over a communications network. Information carriers suitable for embodying computer program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices. The information carriers can, for example, be EPROM, EEPROM, flash memory devices, magnetic disks, internal hard disks, removable disks, magneto-optical disks, CD-ROM, and/or DVD-ROM disks. The processor and the memory can be supplemented by, and/or incorporated in special purpose logic circuitry".
As such, this disclosure supports the finding that no more than a general purpose computer, performing generic computer functions, is required by the claims.
Viewed as a whole, these additional claim elements do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See Alice Corporation Pty. Ltd. v. CLS Bank Int'/ et al., No. 13-298 (U.S. June 19, 2014).
As a result of the above analysis, claim 1, as well as claim 10, do not appear to be patent eligible under 101.
Dependent claims 2-9 and 11-19 recite additional elements that merely narrow the previously recited abstract idea. When viewed as a whole, the additional elements amount to no more than mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)).
Thus claims 1-19 are not patent eligible under 101.
Claim Rejections - 35 USC§ 102
7. 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 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.
8. 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)(2) the claimed invention was described in a patent issued under section 151,
or in an application for patent published or deemed published under section
122(b), in which the patent or application, as the case may be, names another
inventor and was effectively filed before the effective filing date of the claimed
invention.
9. Claims 1-10 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Shivam (Optimization of Driver Shift (and Break) Schedule using Simulated Annealing in Ride-Pooling Service).
Regarding claim 1, Shivam discloses a communications interface configured (Page 8 Paragraph 1) to:
receive a desired budget for the optimized supply planning over a future period of time (i.e., operational cost; Page 4, paragraph 2);
receive one or more shift constraints for the optimized supply planning (Page 11, paragraph 1);
at least one processor configured to determine expected demand for the future period of time based on historical demand data (Page 1, last paragraph);
determine quality of service as a function of a number of vehicles for each of a plurality of time bins based on the expected demand (Page 17, last paragraph); and
determine optimized shifts for the rideshare management system that maximizes the quality of service based on the function in each of the plurality of time bins, the one or more shift constraints, the desired budget or any combination thereof (see entire page 1 of Shivam).
Regarding claim 2, Shivam further teaches assign drivers to each of the optimized shifts based on driver availability, driver preferences, labor rules, salaries, or any combination thereof ( see entire page 1 of Shivam)
Regarding claim 3, Shivam further teaches wherein the budget is total cost for operation over the future period of time, number of hours for vehicles over the future period of time, or any combination thereof (Page 2, last paragraph).
Regarding claim 4, Shivam further teaches wherein determining optimized shifts is further based one or more set of predetermined shifts for the optimal supply planning, one or more supply plan objectives or any combination thereof (Page 12, paragraph 3).
Regarding claim 5, Shivam further teaches wherein determining the quality of service is further based on machine learning (Page 14, paragraph 1) .
Regarding claim 6, Shivam further teaches wherein determining the quality of service is further based on expected weather, expected time of day, or any combination thereof (Page 16, paragraph 4).
Regarding claim 7, Shivam further teaches wherein determining the quality of service is further based on met demand, on-time performance, time it takes to serve an on-demand ride, or any combination thereof (Page 12, paragraph 3).
Regarding claim 8, Shivam further teaches determining the optimized shifts further comprises: determining contribution that a shift at a start of the shift, end of a shift or around a break time during the shift or any combination thereof has on the number of available vehicles (i.e., a shift, in turn, is determined by its start and end time). Note Page 19, paragraph 2 of Shivam.
Regarding claim 9, Shivam further teaches wherein the contribution is a fractional contribution to the number of available vehicles. Note entire page 27 of Shivam.
Regarding claim 10, Shivam discloses a communications interface configured to receive a desired rate of met demand (Page 8 Paragraph 1), receive one or more shift constraints, or any combination thereof planning (Page 11, paragraph 1); at least one processor configured to determine expected demand for a future period of time based on historical demand data (Page 1, last paragraph), determine required supply for the future period of time based on the expected demand and the desired rate of met demand (Page 4, paragraph 2), determine optimized shifts for a plurality of vehicles in the rideshare management systems based on the determined required supply, one or more supply plan objectives, one or more shift constraints, or any combination thereof (see entire pages 1 of Shivam and Page 7, first and second paragraph).
Regarding claim 11, Shivam further teaches wherein determining optimized shifts is further based one or more set of predetermined shifts for the optimal supply planning, one or more supply plan objectives (Page 12, paragraph 3).
Regarding claim 12, Shivam further teaches assign drivers to each of the optimized shifts based on the determined optimized shifts (Page 9, paragraph 3).
Regarding claim 16, Shivam discloses wherein determining required supply for the future period of time is further based on number of bookings for a future period, expected number of passengers vs. expected number of bookings, weather prediction, or any combination (Page 16, paragraph 4).
Regarding claim 18, Shivam further discloses determining contribution that a shift at a start of the shift, end of a shift or around a break time during the shift or any combination thereof has on a number of available vehicles (i.e., a shift, in turn, is determined by its start and end time). Note Page 19, paragraph 2 of Shivam.
. Regarding claim 19, Shivam further discloses wherein the contribution is a fractional contribution to the number of available vehicles. Note entire page 27 of Shivam.
.
Claim Rejections - 35 USC§ 103
10. 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 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.
11. 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.
12. Claims 13-15 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Shivam (Optimization of Driver Shift (and Break) Schedule using Simulated Annealing in Ride-Pooling Service) as applied to claim 1 above in view of LI et al (U.S. Patent Publication No. 20220277652).
Regarding claim 13, Shivam fails to teach but LI et al teach determine demand level for each of a plurality of time bins to create an expected demand for each time bin based on historical met demand, determine a percentage of demand met as a function of vehicle supply for each of the plurality of time bins based on the historical met demand, and create a target supply vector based on the function (Paragraph [0081]).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of the effective filing date of the claimed invention to have modified the system of Shivan to have incorporated the teachings of LI et al, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the result of the combination were predictable.
Regarding claim 14, Shivan fails to teach but LI et al teach wherein determining the demand level is based on machine learning (Paragraph [0081]). It would have been obvious to one of ordinary skill in the art, at the time of the effective filing date of the claimed invention to have modified the system of Shivan to have incorporated the teachings of LI et al, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the result of the combination were predictable.
Regarding claim 15, Shivam further discloses wherein the demand level for each of the plurality of time bins is further based on expected (Page 16, paragraph 4)).
Regarding claim 17, Shivam fails to teach but LI et al teach wherein determining optimized shifts is further based on the target supply vector (Paragraph [0081]).
Therefore, it would have been obvious to one of ordinary skill in the art, at the time of the effective filing date of the claimed invention to have modified the system of Shivan to have incorporated the teachings of LI et al, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the result of the combination were predictable.
Conclusion
13. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. As per attached PTO 892 form.
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/RJ/
/ROMAIN JEANTY/Primary Examiner, Art Unit 3624