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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06/16/2026 has been entered.
Status of Claims
Claims 1-2, 4-7, 9-10, and 12 were rejected in the Final Office action mailed on 03/27/2026. Applicant’s amended claimset, entered on 06/16/2026, amended Claims 1, 6, and 12. Herein this Non-Final Office Action, Claims 1-2, 4-7, 9-10, and 12 are rejected.
Priority
Acknowledgment is made of applicant’s claim for National Stage under 35 U.S.C. 371 and foreign priority. The certified copies of parent Application PCT/SG2022/050250, filed on 04/27/2022, and parent Application SG10202104668R, filed on 05/05/2021, have been entered on 07/10/2023.
Response to Arguments
Applicant’s arguments filed 06/16/2026, with respect to Rejections under 35 U.S.C. 112(b) for Claims 1-2, 4-7, 9-10, and 12, have been fully considered and are persuasive.
Applicant’s arguments filed 06/16/2026, with respect to Rejections under 35 U.S.C. 101 for Claims 1-2, 4-7, 9-10, and 12, have been fully considered and are not persuasive.
On Pages 8-9, regarding Step 2A: Prong One, Applicant argues that the claims are not “directed to” mathematical concepts nor certain methods of organizing human activity, but “the claim is directed to a specific computer-implemented method executed by a microprocessor for generating vehicle routes by: [performing the claimed operations].” Examiner does not agree.
First, Examiner notes that Step 2A: Prong One merely asks if the claim “recites” a judicial exception. Much of Applicant’s arguments relate to the additional elements supporting that the claims are not “directed to” the recited abstract idea, and does not seem to dispute that the claim “recites” an abstract idea. In support of compact prosecution, Examiner will respond to arguments as if related to Step 2A, as a whole, which asks if the claims are “directed to” a recited judicial exception.
Examiner responds that the additional elements, i.e. computer microprocessor implementation, does not integrate the recited abstract idea into a practical application, and therefore the claims are “directed to” the recited abstract idea, as discussed in greater detail below.
On Pages 9-10, Applicant further argues “This is thus not a case where the claim merely stores, analyses, and outputs an information, and invokes a computer as a tool. The claim recites a concrete, rule based computational workflow that operates only on groupable bookings, re-uses cached groupability values rather than recomputing and processing large data sets of pick-up and drop-off locations to identify cost ratio, and performs an iterative route determination search to determine the final vehicle route in a predetermined time limit of 2 seconds.” Applicant further argues that “Independent claim 1 does not merely recite a formula in isolation to determine cost ratio; it integrates a cost ratio computation into a larger technological process that involves caching, iterative use of groupability values, heuristic VRP solving under strict time limits, and generation of a final route without re-calculation of ungroupable bookings. As in Diamond v. Diehr, where the claimed invention used a mathematical formula as part of a larger process for curing rubber, here the cost ratio computation is only one step within a defined computer-implemented method that improves the operation of a computerized vehicle routing system.” Applicant further argues that “the claimed ‘use’ of cached groupability values is expressed in view of the dual uses of the cached groupability values: 1) for identifying groupable and not-groupable bookings, and 2) for quick execution of the VRP solver by utilizing the cached groupability values within a strict time limit of 2 seconds to determine the final route, since retrieving a stored value from cache is faster than retrieving from the memory to execute the VRP solver within the 2 seconds time limit.” Examiner does not agree.
Examiner responds, first, that the operations of optimizing a route, by performing certain calculations and certain determinations, is a part of the recited abstract idea as discussed in greater detail in the rejection section below. This abstract idea includes the re-use of certain previously calculated parameters, e.g. having a human re-use a previously calculated variable in a subsequent calculation of would likely be a part of an abstract idea, and the time constraint, e.g. having a human come up with the best route that they can within a fixed time period would also likely be a part of an abstract idea.
Examiner responds that merely executing an abstract idea, which could include a workflow of operations, on a computer does not ensure patent subject matter eligibility. A cache is computer memory, which is a component of nearly any computer system, that provides faster loading to the processer for the purposes of storing data that is repeatedly loaded onto the processor as discussed in AWS and Electrical Engineering Stack Exchange. Storing and re-accessing certain information that is used to solve a VRP does not provide a non-generic use of a computer. See Bentley and Helsgaun.
Additionally, Examiner notes that the claims do not provide a comprehensive set of limitation regarding how each type of claimed data is stored and accessed in a specific type of storage medium throughout the computation, which could yield a patent eligible improvement to the functioning of computer memory in the context of executing a VRP solver, but merely limits some data to be stored in a cache.
Examiner responds that the claimed time constraint merely limits the time spent trying to determine the optimal route, and does not ensure that the quality of the route determined within the time constraint be just as good as the quality of the route determined if given infinite time to determine the optimal route. Specification ¶¶20-21 and ¶¶27-35 indicates that the iterative search includes checking whether certain route configurations have “a lower cost than the best cost found so far.” A person of ordinary skill in the art would understand that in an example embodiment, where there are an extraordinarily high number of bookings being optimized on a small computer, the time constrain would be achieved by terminating the search without calculating every possible configuration of bookings applied to the route. Thus, the time constraint does not represent an improvement to the functioning of a computer, but merely is an advantageous part of the recited abstract idea. Because the time constraint represents an improvement in the abstract idea itself, not in the technology itself, the claims are distinguishable from Diamond v. Diehr.
On Pages 10, Applicant further argues “Amended independent claim 1 is therefore directed to a specific asserted improvement in computer technologies associated with vehicle navigation systems namely, a structured, real-time computational mechanism that pre-computes and caches groupability values, uses the cached groupability values in an iterative heuristic search executed by the VRP solver under strict time constraints to obtain a final route, and appends ungroupable bookings without re-computation to the obtained final route. This is not a statement of an abstract goal or mathematical idea in isolation, but a defined computer-implemented method that improves a vehicle dispatch system by reducing computational overheads by using cached groupability values not only in identifying groupable and not groupable bookings but also in performing iterative heuristic search by the VRP solver so that cost ratio does not require any re-computation and delivering faster and optimized output with lesser calculations which is achieved by performing computations only on the groupable bookings. Accordingly, amended independent claim 1 is not directed to organising human activity or a mathematical concept, but to a technological improvement in the internal operation of a real-time vehicle navigation system. Further, the Application in paragraph [0045] recites, ‘[ v ]arious embodiments disclose an improvement to VRP solver or VRP solver including the improvement, so that the vehicle routing problem is solvable under real case constrains, such as time constraints and computation resources constraints. Reducing the problem size makes the process or the VRP solver more efficient and faster in terms of computing technology or computing resources.’ Therefore, amended independent claim 1 recites technological improvement to the computer system by reducing processing overheads and is not directed to the abstract idea of organising human activity or a mathematical concept. Accordingly, amended independent claim 1 is not directed to an abstract idea under Prong One of Step 2A.” Examiner does not agree.
MPEP 2106.05(f) states “‘claiming the improved speed or efficiency inherent with applying the abstract idea on a computer’ does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).”
MPEP 2106.05(a)I states “Examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality:
. . .
ii. Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016);
iii. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential);
iv. Recording, transmitting, and archiving digital images by use of conventional or generic technology in a nascent but well-known environment, without any assertion that the invention reflects an inventive solution to any problem presented by combining a camera and a cellular telephone, TLI Communications, 823 F.3d at 611-12, 118 USPQ2d at 1747;
v. Affixing a barcode to a mail object in order to more reliably identify the sender and speed up mail processing, without any limitations specifying the technical details of the barcode or how it is generated or processed, Secured Mail Solutions, LLC v. Universal Wilde, Inc., 873 F.3d 905, 910-11, 124 USPQ2d 1502, 1505-06 (Fed. Cir. 2017); . . .”
Examiner asserts a hypothetical method of typing 2x5 into a calculator, instead of typing 2+2+2+2+2, which may result in less computational resources and a quicker computation of the result. However, such advantage may not necessitate an improvement in the calculator itself, but could be an improvement in the mathematical operations itself.
Examiner responds that, although the claims do not purely recite an abstract idea (i.e. additional computer elements applying the recited abstract idea), the additional elements do not integrate the recited abstract idea into a practical application. The abstract idea includes precomputing groupability values, re-using those values, and communicating the route to a driver. The advantages of ¶45 are improvements in the abstract idea itself, not improvements to a computer. Additionally, the advantages of using computer components, including cache, are analogous to claiming the speed inherent with the use of a computer as in MPEP 2106.05(f) and Examples ii-v of MPEP 2106.05(a). Applicant has failed to show a technical explanation of an improvement in technology (not an abstract idea), beyond a conclusory manner, as required by MPEP 2106.05(a). Thus, any reduction in computational resources asserted by applicant are either: the result of an improvement in the abstract idea (e.g. reduction in problem size or providing a more cost-effective route to a driver), or are asserted in a conclusory manner without sufficient technical explanation (e.g. use of cache).
On Pages 10-11, regarding Step 2A: Prong Two, Applicant argues that the claims recite additional elements that integrate the judicial exception into a practical application. Applicant notes that the analysis of Step 2A Prong Two requires the evaluation of the claim “as a whole” per the MPEP. Specifically, Applicant argues that “the Office Action selectively extrapolates certain claim features as ‘mathematical concepts’ and others as ‘organizing human activity,’ instead of considering the claim as a whole.” Applicant further argues “The claim limitations recite steps carried out by the microprocessor as part of the claimed computational workflow. The heuristic VRP solver functionally determines which combinations of bookings, i.e., groupable bookings, are optimized into a route under strict time constraints, and how cached groupability values are used to accelerate iterative search to determine the final route. Thus, the limitations of independent claim 1, when considered as a whole, transforms the computations into a coordinated, computer-implemented method that improves computer-based routing by enabling real-time, data-driven optimized route generation tied to structured caching that reduces computational overhead.” On Pages 11-12, Applicant argues “Further, the transmission step (the step of transmitting the final vehicle route via a communication interface to a driver device) is neither a mere insignificant post-solution activity to manage personal behaviour nor a generic act of data output performed after the Application has already achieved its result; it is the mechanism by which the system operationalizes the routing outcome. The final route is expressly required to be transmitted to a driver device for execution, and amended independent claim 1 requires that the transmission of the final route results in re-routing of a driver vehicle. This limitation functionally ties the computational analysis to ongoing system operation and prevents stale or inconsistent routing behavior which would result in unnecessary recomputation of the final route. Thus, said step is not merely managing personal behaviour but instead optimizing computational load by using cached groupability values in multiple ways, i.e., in identifying groupable and not groupable bookings and in performing the iterative search through the VRP solver by using cached groupability values that eliminates the need to re-compute cost ratios in determining the final route.” Examiner does not agree.
Examiner responds that the claims were looked at “as a whole,” and determined to merely apply the abstract idea (i.e. performing certain calculations and operations to communicate a more cost-effective route to a service provider) using generic computer components in their conventional way (i.e. storing data accessed repeatedly in a cache, using a computer to perform calculations more quickly than by a human). The additional elements, when viewed in the claim as a whole, do not transform the claim into an improvement to a computer (i.e. integrate the recited abstract idea into a practical application), but merely perform generic computer functions (e.g. storing data in cache for re-use or using computers to transmit a message) to apply the recited abstract idea. Therefore, the claim does not recite additional elements that integrate the recited abstract idea into a practical application.
On Pages 12-13, Applicant argues that “the assertion in the Office Action that independent claim 1 ‘merely uses additional elements in their ordinary capacity’ is inconsistent with the claim language. Claim 1 does not simply automate an abstract decision or economic judgment; it recites a technological method that governs how the system itself operates in real time. In particular, the claim requires the microprocessor to pre-compute and cache groupability values, classify bookings based on threshold cost ratios as groupable or un-groupable bookings, execute a heuristic VRP solver under strict time limits with iterative use of cached groupability values, append ungroupable bookings without recomputation to a final route, and transmit the final route to a driver device for execution. Crucially, amended claim 1 improves the efficiency of computer-based processing by reducing re-computation, leveraging cached values wherever possible, and enabling time-bounded heuristic solving. This directly enhances the functioning of the computer system itself, providing a technological improvement in how complex routing problems are solved under real-time constraints that reduce computational overload. Further, the amended independent claim 1 executes the VRP solving algorithm in a computer resource efficient manner that minimizes unnecessary re-computation of cost ratios that slows down the output generation efficiency, i.e., final route generation, of a computer system. Indeed, the amended independent claim 1 clearly recites the frequency of the VRP solver, i.e., within a strict time limit of 2 seconds and further recites the VRP epoch trigger, i.e., in response to obtaining the plurality of bookings. Therefore, independent claim 1, as amended, clearly recites the limitations identified in the Advisory Action, and thus addresses the deficiencies pointed out in the amended independent claim 1.” Examiner does not agree.
Examiner responds that claimed limitations of pe-calculating groupability values, classify bookings based on threshold cost ratios as groupable or un-groupable bookings, execute a heuristic VRP solver under strict time limits with iterative use of groupability values, append ungroupable bookings without recalculating the initial route, determining the final route within a time constraint, and transmit the final route to a driver for execution, are all a part of the abstract idea. The reduction of complexity is the result of the abstract idea itself, and the asserted advantages would likely be actualized if performed by a human without a computer.
The use of a processor to perform iterative calculations, cache to store VRP parameters that accessed multiple times, and driver device to receive a message, are conventional uses of computer components. Therefore, the claims to not provide a patent subject matter eligible improvement under MPEP 2106.05(a).
On Pages 13-14, regarding Step 2B, Applicant argues “Notwithstanding the above remarks under Step 2A, arguendo, that independent claims 1, 6, and 12 are directed to an abstract idea/judicial exception as the Office Action contends, the claim as a whole recites a specific, ordered combination of: (1) obtaining booking data packets with pick-up and drop-off locations; (2) estimating groupability values for each booking pair by computing cost ratios; (3) storing the groupability values in a cache for use during an iterative vehicle route determination search; (4) classifying bookings as groupable or ungroupable based on a threshold associated with cost ratios; (5) executing a heuristic VRP solver solely on the groupable bookings within a strict time limit of less than two seconds, such that the VRP solver uses cached groupability values to perform iterative search for determining a final route; (6) appending ungroupable bookings as isolated routes without re-computation to the final route; and (7) transmitting the final vehicle route to a driver device for re-routing. This specific, ordered combination recited in independent claim 1 is not routine or conventional. Instead, the claim recites an inventive concept because, as an ordered combination, it addresses specific deficiencies of conventional vehicle dispatch and routing methods. As explained in the claimed Application, conventional routing techniques suffer from systemic inefficiencies when attempting to solve large-scale vehicle routing problems: repeated re-computation of final route by including the ungroupable bookings, excessive processing time, stale routing decisions, and inability to meet real-time constraints. These behaviors cause repeated reprocessing, increased computational overhead, and degraded system responsiveness. The amended independent claim 1 overcomes these deficiencies by introducing a structured, real-time computational mechanism that pre-computes and caches groupability values, uses the groupability values in an iterative heuristic search executed by the VRP solver under strict time constraints, and appends ungroupable bookings without re-computation to the final route. Critically, this arrangement reduces computational overheads by avoiding repeated calculations of cost ratio to determine groupability values, enables faster and optimized route generation with fewer calculations, and ensures real-time responsiveness by limiting computation to groupable bookings. This is not a generic computer performing routine data processing; it is a specific, non-conventional arrangement of steps that alters how the system behaves over time to reduce unnecessary re-computation and resource contention. Accordingly, independent claim 1 is not directed to organizing human activity or a mathematical concept, but to a technological improvement in the internal operation of a real-time vehicle dispatch system. Under BASCOM Global Internet Services, Inc. v. AT&T Mobility LLC, an inventive concept may arise from such a non-conventional, non-generic ordered combination of known elements. Here, the inventive concept lies in the integration of caching, multiple use of cached groupability values, heuristic solving under strict time limits, and selective computation only on groupable bookings, which together improve the functioning of the computer system itself. In view of the foregoing remarks, amended independent claim 1, when taken as a whole, qualifies as significantly more than an abstract idea.” Examiner does not agree.
Examiner responds that, as discussed in the no art rejection section, the use of a cache in a VRP solver to provide quick access to data that is repeatedly accessed is shown by at least Bentley and Helsgaun. The use of a cache, along with the other additional elements, when viewing the claim as a whole, does not provide an improvement to technology under MPEP 2106.05(a) as discussed in greater detail above.
Examiner responds that the time limitation to heuristic does not improve the functioning of a computer. A person of ordinary skill in the art understands that the vehicle routing problem (or traveling salesman problem) is a field of mathematics that predates the invention of the computer, for which several approaches can be used to provide a solution, the trade-off being commonly known between time/effort spent calculating, and quality of final route, i.e. brute force calculation of every possible route taking the most time/effort, but ensuring the final route is the actual best route.
Applicant’s disclosure does not provide any specific explanation of the search algorithms used that enables to achieve a certain level of quality within the 2 second time constraint. Therefore, the broadest reasonable interpretation of the time constraint would include merely stopping the search at that time. Thus, the time constraint remains a part of the abstract idea, and does not provide an improvement in technology. Similarly the pre-filtering of groupable and ungroupable bookings, along with reuse of the groupability value, is a part of the abstract idea. Any advantages that result from these limitations would be an improvement in the abstract idea itself, not an improvement in the functioning of a computer.
Claim Interpretation
Claim 1 recites “wherein the transmission of the final vehicle route on the driver device results in re-routing of a driver vehicle” (emphasis added) at the end of the claim. The limitation that the transmission of the final vehicle route “results in re-routing of a driver vehicle” merely states that the “final vehicle route” be different than whatever the route of “driver vehicle” was before the transmission, i.e. the claimed “re-routing” is not a reference to, or related to in any way, the claimed “initial vehicle route.” Thus, this limitation is analogous to claiming “wherein the transmission of the final vehicle route on the driver device results in altering, changing, or modifying a driver vehicle’s current driving, route, or travel plan.”
Such interpretation is extended to independent Claims 6 and 12, that recite similar language and dependent Claims 2, 4-5, 7, and 9-10.
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 1-2, 4-7, 9-10, and 12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Overview of Analysis
The subject matter eligibility analysis comprises: Step 1 (i.e. Does the claim fall within one of the four stator categories, e.g. process, machine, manufacture, or composition of matter?), Step 2A (Is the claim “directed to” a judicial exception, e.g. abstract idea, natural phenomena, or law of nature?), and Step 2B (i.e. Does the claim recite “additional elements” that amount to “significantly more” than the judicial exception?). MPEP 2106.III.
Step 2A is a two-prong analysis. MPEP 2106.04. Step 2A Prong-One first determines whether the claim merely “recites” (i.e. “sets forth” or “describes”) a judicial exception. MPEP 2106.04.II.A.1. Then, Step 2A Prong-Two determines if the claim “recites” “additional elements” that integrate the recited judicial exception into a practical application (e.g. if the recited additional elements do not “integrate the recited judicial exception into a practical application,” then, Step 2A would conclude that the claim is “directed to” the recited judicial exception.). MPEP 2106.04.II.A.2.
Step 1
Claims 1-2 and 4-5 recite a method (i.e. a process), Claims 6-7 and 9-10 recite a system (i.e. a machine or manufacture), and Claim 12 recites a non-transitory computer-readable medium (i.e. a machine or manufacture), and. Therefore, Claims 1-2, 4-7, 9-10, and 12 all fall within the one of the four statutory categories of invention of 35 U.S.C. 101.
Step 2A, Prong One
Independent Claim 1 recites the abstract idea of:
“. . . obtaining, a plurality of bookings, each booking of the plurality of bookings comprising a pick-up and a drop-off location received
prior to determining an initial vehicle route, estimating, for each combination of two bookings of the plurality of bookings, a groupability value by determining a cost ratio of the combination as a ratio of the cost of the combination to the sum of the cost of the two bookings taken separately,
wherein a higher groupability value represents a lower cost ratio below a pre-determined threshold, and a lower groupability value represents a higher cost ratio above the pre-determined threshold;
storing the groupability values . . . fouse during an iterative vehicle route determination search;
identifying, based on the groupability values . . . , all bookings that are not groupable to any other booking of the plurality of bookings due to all associated cost ratios exceeding the pre-determined threshold, as ungroupable bookings;
identifying, based on the groupability values . . . , all bookings that are groupable to at least one other booking of the plurality of bookings due to at least one associated cost ratio below the pre- determined threshold, as groupable bookings;
determining the initial vehicle route in response to obtaining the plurality of bookings by executing a heuristic a vehicle routing problem (VRP) solver solely on the groupable bookings within an allotted time limit of less than two (2) seconds, wherein the VRP solver determines an optimized route given the groupable bookings, wherein the heuristic VRP solver uses the groupability values stored . . . to reduce re-computation of the cost ratio by performinggroupablebookings retrieved . . . to generate the optimized route;
adding the ungroupable bookings to the initial vehicle route as isolated pick-up and drop-off routes appended to the optimized route without re-computing the optimized route to produce a final vehicle route including a sequence of pick-up locations and drop-off locations; and
transmitting the final vehicle route . . . to a driver . . . for execution of the final vehicle route, wherein the transmission of the final vehicle route on the driver device results in re-routing of a driver vehicle
The limitations stated above are processes/ functions that under broadest reasonable interpretation covers (1) obtaining bookings, (2) estimating a groupability factor for each combination of bookings using cost ratios before determining an initial vehicle route, (3) storing the groupability values for later user, (4) identifying bookings as groupable or not groupable by applying a threshold to the cost ratios, (5) determining an initial route using a VRP solver to optimize route given the groupable bookings within two seconds by performing an iterative search using the stored groupability values, (6) adding the ungroupable bookings as isolated pick-up and drop-off routes to create a final route, appending the optimized route (i.e. not re-computing the optimized route), and (7) transmitting the final route to be executed resulting in the re-routing of the vehicle, all of which are:
mathematical relationships (i.e. cost ratio and groupability value) and mathematical calculations (i.e. vehicle routing problem (VRP) solver including iterative search), which are mathematical concepts, an abstract idea, under MPEP 2106.04(a)(2)I,
managing personal behavior by following rules and interacting between people by communicating information (i.e. determining and executing a route is determining and following rules or instructions) and commercial or legal interactions (i.e. grouping bookings of a service to be provided based on a certain metric is “marketing or sales activities or behaviors”), which are certain methods of organizing human activity, an abstract idea, under MPEP 2106.04(a)(2)II, and
evaluation and judgment (i.e. determining groupability and optimal route) which are mental processes, an abstract idea, under MPEP 2106.04(a)(2)III.
The mere the recitation of generic computer components (i.e., the “computer,” “microprocessor,” “memory,” “data packet,” “cache,” “communication interface,” and “driver device”) as additional elements implementing the identified abstract idea does not take the claim out of the certain methods of organizing human activity, mathematical concepts, or mental processes groupings. MPEP 2106.04. Therefore, Claim 1 “recites” an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. Claim 1 as a whole amounts to: (i) merely invoking generic components as a tool to perform the abstract idea or “apply it” (or an equivalent) and (ii) generally links the use of a judicial exception to a particular technological environment or field of use. The claim recites the additional elements of:
(i) “computer” implementing the method,
(ii) “microprocessor,”
(iii) “memory,”
(iv) “data packet,”
(v) “cache” storing information,
(vi) “communication interface” transmitting data, and
(vii) “driver device.”
The additional elements of the (i) computer (Fig. 5 and ¶36 shows “computer 402.” ¶14 indicates that the computer may be “a server or cloud.”), (ii) “microprocessor” (Fig. 5 and ¶36 shows “microprocessor 410”), (iii) “memory” (Fig. 5 and ¶36 shows “memory 420”), (iv) “data packet” (¶14 shows “Each booking of the plurality of bookings may include a pick-up and a drop- off location and may be encoded in a data packet.”), (v) cache (Fig. 5 and ¶40 shows “the memory 420 may include a groupability cache configured to store estimated groupabilities including the groupability for each combination of two bookings.”), (vi) “communication interface” (Fig. 5 and ¶36 shows “communication interface 430”), and (vii) driver device (Fig. 5 and ¶43 shows “one or more vehicles or drivers 470, 480, 490.”), are recited at a high-level of generality, such that, when viewed as whole/ordered combination (Fig. 5 shows elements in combination), they amount to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
The (i) “computer,” (ii) “microprocessor,” (iii) “memory,” (iv) “data packet,” (v) “cache,” (vi) “communication interface,” and (vii) “driver device,” when viewed as whole/ordered combination (Fig. 5 and ¶36 shows elements in combination.), does no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. computer environment) (See MPEP 2106.05(h)).
Accordingly, these additional elements, when viewed as a whole/ordered combination (Fig. 5 shows elements in combination), do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements amount to no more than: (i) “apply it” (or an equivalent) and (ii) generally link the use of a judicial exception to a particular technological environment or field of use, and are not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)) and (ii) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional elements of the (i) “computer,” (ii) “microprocessor,” (iii) “memory,” (iv) “data packet,” (v) “cache,” (vi) “communication interface,” and (vii) “driver device,” do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination (Fig. 5 shows elements in combination), nothing in the claims adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, the claim is ineligible.
Dependent Claims 2 and 4-5 recite the abstract idea of:
“. . . generating, for each booking, a cost ranking based on the cost ratio for each position in the initial vehicle route, and wherein the VRP solver updates the initial vehicle route based on the ranking” (Claim 2);
“determining a feasibility of the combination, wherein the combination is unfeasible if at least one constraint of a plurality of constraints is not met, and wherein the combination is feasible if all constraints of the plurality of constraints are met; if the combination is unfeasible, the groupability value is set to represent that the combination is unfeasible, wherein determining an initial vehicle route ignores combinations that are unfeasible” (Claim 4); and
“. . . wherein the VRP solver has an allotted time limit to determine the initial vehicle route” (Claim 5).
Dependent Claims 2 and 4-5, have been given the full two-prong analysis including analyzing the further elements and limitations, both individually and in combination. When analyzed individually and in combination, these claims are also held to be patent ineligible under 35 U.S.C. 101. The further limitation of Claims 2 and 4-5 fail to establish claims that are not directed to an abstract idea because the further limitations include (1) generating a cost ranking, (2) storing information, (3) determining feasibility of a combination and setting the groupability value accordingly, and (4) solving math within an allotted time, which merely limit the scope of the abstract idea. The elements of Claims 2 and 4-5 fails to establish claims that are not directed to an abstract idea because the elements merely recite generic computer components similar to the generic computer components of Claim 1 and generally link the abstract idea to a particular technology or field of use (i.e. computer environment) just as in Claim 1. The organization of the further limitations of Claims 2 and 4-5 fail to integrate an abstract idea into a practical application just as discussed above for Claim 1. Additionally, performing the abstract idea of Claim 1 as recited in each of the further limitations of Claims 2 and 4-5, individually or in combination, does not (1) impose any meaningful limits on practicing the abstract ideas, or (2) provide improvements to the functioning of computing systems or to another technology or technical field, just as discussed above regarding Claim 1. Therefore, Claims 2 and 4-5 amount to mere instructions to implement the abstract idea (1) using generic computer components—using the computer, in its ordinary capacity, as a tool to perform the abstract idea, and (2) generally linked to a particular technology or field of use. Because the claims merely use a computer, in its ordinary capacity in a particular field of use, as a tool to perform the abstract idea cannot provide an inventive concept, the elements and limitations of Claims 2 and 4-5 fail to establish that the claims provide an inventive concept, just as in Claim 1. Therefore, Claims 2 and 4-5 fails the Subject Matter Eligibility Test and are consequently rejected under 35 U.S.C. 101.
Claims 6-7 and 9-10 recites elements and limitations that are substantially similar to Claims 1-2 and 4-5 because Claims 6-7 and 9-10 claim a system that embodies the method of Claims 1-2 and 4-5. Therefore, Claims 6-7 and 9-10 are rejected under 35 U.S.C. 101 just as Claims 1-2 and 4-5 is rejected under 35 U.S.C. 101 as discussed above.
Claim 12 recites elements and limitations that are substantially similar to Claim 6. Therefore, Claim 12 is rejected under 35 U.S.C. 101 just as Claim 6 is rejected under 35 U.S.C. 101 as discussed above.
Reasons for Withdrawal of Art Rejection
Claims 1-2, 4-7, 9-10, and 12 are not rejected over the prior art of record.
The closest prior art of record is:
GB-2397683-A (“Olmi”);
US-20150206437-A1 (“Fowler”);
“Database Caching” (“AWS” Feb 13, 2021, https://web.archive.org/web/20210213122815/https://aws.amazon.com/caching/database-caching/);
KR-102091019-B1 (“Kim”);
US-20220036309-A1 (“Neumann”);
US-20030182052-A1 (“DeLorme”);
US-20110112759-A1 (“Bast”);
CN-108921472-A (“Liu”);
“K-d Trees for Semidynamic Point Sets” (“Bentley” 1990, https://dl.acm.org/doi/pdf/10.1145/98524.98564);
“An effective implementation of the Lin-Kernighan traveling salesman heuristic” (“Helsgaun” 10/01/2000, https://www.sciencedirect.com/science/article/pii/S0377221799002842?via%3Dihub); and
“What information exactly does an instruction cache store” (“Electrical Engineering Stack Exchange” 05/13/2019, https://electronics.stackexchange.com/questions/438294/what-information-exactly-does-an-instruction-cache-store).
The Following is an examiner’s statement of reasons for no art rejections:
Olmi shows iteratively assigning ride requests to vehicle plans for specific vehicles that satisfy the request requirements. The system utilizes a grouping algorithm to ensure that rides grouped together do not exceed a threshold level of additional travel time. An “efficiency ratio” (i.e. cost ratio) is calculated for each itinerary by comparing the direct (un-grouped) travel time versus the individual’s travel time in the group. However, this operation occurs after the optimized route, which can include an “isolated” ride, is created. Although this operation is performed interactive, an “isolated” ride for “Class B” rides (i.e. rides that have already been assigned to a vehicle’s travel plan), (1) is a part of the initial travel plan, and (2) could be later grouped with other rides based on the efficiency ratio criteria being satisfied by a subsequent ride request.
Fowler shows calculating a cost ratio between each passenger’s route taken “solo” versus as part of the shared vehicle. However, Fowler does not disclose adding rides that fail to meet the threshold as “isolated” rides to the travel plan.
AWS shows the advantages of cache memory. As the claims do not include storing certain data in cache memory and other data in non-cache memory, AWS could generally be applied to storing data in cache memory.
Kim shows efficient matching and performance of simultaneous rides. I concurrent ride may be accepted based on how much the vehicle must deviate from its current route to accommodate the new request. Each user has their own ratio threshold that must be satisfied, which signifies their tolerable transportation efficiency. If the new request does not satisfy each current rider’s threshold, the request is not accepted.
Neumann shows grouping delivery items to be transferred together to find an optimal path of transfer, and providing instructions on which orders to be grouped together.
DeLorme shows providing vehicle routing directions (i.e. sequence of destinations) that combine different points of interest. They system determines potential new waypoints (i.e. points of interest) that could be added to the user’s travel plan.
Bast shows planning optimal public transportation routes. Each transportation “line” has a fixed start point and a fixed end point. The system optimizes an optimal journey in response to user queries utilizing pre-processing.
Liu shows pre-processing orders into cluster based on similarity of locations. However, Liu does not include adding ungroupable orders as “isolated” routes to the final transportation plan.
Bentley shows K-d search caching method that keeps data cached as the points of the traveling are updated, i.e. some points remain while others are deleted or added, so the cached tree is not completely rebuilt.
Helsgaun shows that distances between nodes are saved in a cache so that the computational efficiency of cache is realized next time the distance between nodes needs to be computed.
Electrical Engineering Stack Exchange shows that a cache stores execution instructions, i.e. the program itself, so that when instructions need to be repeated in iterating a loop, the instructions of the previous iteration remain in the cache.
Generally, the closest prior art teaches either (1) grouping passengers while not grouping others using a threshold (Olmi, Fowler, Kim, Neumann, and Lui), (2) calculating a groupability value based on a cost ratio (Olmi, Fowler, Kim, and DeLorme), (3) use of a cache for memory (AWS, Bentley, Helsgaun, and Electrical Engineering Stack Exchange), and (4) a vehicle route including a mixture of group rides and isolated rides (Olmi, Fowler, and Bast).
With respect to independent Claim 1, representative of independent Claims 1, 6, and 12, the closest prior art, taken individually and in an ordered combination, does not explicitly or implicitly disclose the specific ordered combination of features that include:
“prior to determining an initial vehicle route, estimating, for each combination of two bookings of the plurality of bookings, a groupability value by determining a cost ratio of the combination as a ratio of the cost of the combination to the sum of the cost of the two bookings taken separately, . . . ;
identifying, based on the groupability values, all bookings that are not groupable to any other booking of the plurality of bookings due to all associated cost ratios exceeding the pre-determined threshold, as ungroupable bookings;
identifying, based on the groupability values, all bookings that are groupable to at least one other booking of the plurality of bookings due to at least one associated cost ratio below the pre- determined threshold, as groupable bookings;
determining the initial vehicle route in response to obtaining the plurality of bookings by executing a heuristic vehicle routing problem (VRP) solver solely on the groupable bookings . . . , wherein the VRP solver determines an optimized route given the groupable bookings; . . .
adding the ungroupable bookings to the initial vehicle route as isolated pick-up and drop-off routes appended to the optimized route without re-computing the optimized route to produce a final vehicle route . . . ;
transmitting the final vehicle route to a driver device for execution of the final vehicle route.”
(Emphasis added).
The key points of distinction over the prior art are that the feature of the claims include that: the groupability value is “for each combination of two bookings” (e.g. for bookings A,B, C, and D there is a groupability value for A&B, A&C, A&D, B&C, B&D, and C&D), the identification of a single booking as being “groupable” or “ungroupable” is based on if any of the cost ratios associated with that booking (i.e. cost ratio’s for each pair of bookings that the single booking is associated with) satisfy a threshold, applying the VRP solver only to “groupable” bookings to create an “initial vehicle route,” adding the “ungroupable” bookings to the initial vehicle route as “isolated pick-up and drop-off routes” (i.e. while the vehicle is traveling between the pick-up and drop-off locations for an “ungroupable” booking, no other booking is being advanced) to create “a final vehicle route,” and the final vehicle route is transmitted to driver device “for execution of the final vehicle route” (i.e. “ungroupable” bookings are not held in a pool with hopes of later being groupable with subsequent bookings, but instead are executed as an isolated portion of the “final vehicle route”). These features, in combination, are novel and non-obvious over the prior art of record.
Dependent Claims 2 and 4-5 depend on Claim 1, and Dependent Claim 7 and 9-10 depends on Claim 6, and therefore are also held to be novel and non-obvious over the prior art via dependency.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and is as follows:
“An efficient heuristic for very larger-scale vehicle routing problems with simultaneous pickup and delivery” (“Caveliere” Transportation Research Part E: Logistics and Transportation Review, Vol. 186, June 2024, https://www.sciencedirect.com/science/article/pii/S1366554524001418?via%3Dihub) shows use of cache for cost matrix in VRP solving as a common technique.
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/MATTHEW PARKER GOODMAN/Examiner, Art Unit 3628
/JEFF ZIMMERMAN/Supervisory Patent Examiner, Art Unit 3628
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