DETAILED ACTION
This Non-Final Office action is in response to Applicant’s Amendment filed on 08/07/2026. Claims 1-20 are pending. The effective filing date of the claimed invention is 03/19/2025.
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 1-141 and 16-20 are rejected under 35 U.S.C. 101 because the claims are found to be directed to abstract idea.
Step 1 – Claims 1-14,16 are system/machine claims; claims 17-19 are method claims; and claim 20 is a manufacture claim. Step 1 is satisfied.
Step 2A Prong 1 – Exemplary claim 1 (and similarly claims 17, 20) recites the following abstract idea:
receive a set of trailer transportation jobs, each trailer transportation job comprising a temporal requirement defining conditions to be satisfied by a trailer or a vehicle at a location during a time interval (see MPEP 2106.04(a)(2)(III) citing Electric Power Group);
encode the temporal requirement of each trailer transportation job as a set of constraints on one or more of vehicle motion dynamics, trailer motion dynamics, and energy consumption behavior using a metric temporal logic (MTL) specification (MPEP 2106.05 citing RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) (“Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract”));
solve a constrained optimization problem optimizing a cost function subject to the set of constraints and a set of vehicle operation constraints to generate a plan comprising one or more trailer assignments, vehicle trajectories, and charging actions, wherein the cost function includes a trailer motion cost and an energy consumption cost indicative of a total amount of energy of the fleet of trucks (see MPEP 2106.04(a)(2)(I)(A-C)); and
execute at least a portion of the plan within the logistics environment to control the movement of the trailers by the fleet of vehicles (see MPEP 2106.04(a)(2)(III)(C)).
When viewed alone and in ordered combination, these limitations are found to recite abstract idea.
Step 2A Prong 2 – Claim 1 (and 17, 20) are not found to integrate the underlying abstract idea into practical application. The additional elements of a processor and a memory are recited and used in an “apply it” manner. See MPEP 2106.05(f). When viewed alone and in ordered combination, these additional elements are found to be directed to abstract idea.
Step 2B – Claim 1 is not found to include significantly more. The additional element analysis of Step 2A Prong 2 is equally applied here. Another consideration when determining whether a claim recites significantly more than a judicial exception is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry. This consideration is only evaluated in Step 2B of the eligibility analysis. The courts have recognized the following computer functions as well‐understood, routine, and conventional (WURC) functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
Claim 1 recites receiving data – see MPEP 2106.05(d)(II) i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information) found to be WURC;
Claim 1 recites solving a constrained problem through mathematical calculations – see MPEP 2106.05(d)(II) ii. Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values) found to be WURC.
When viewed alone and in ordered combination, the examiner finds that the claims are directed to abstract idea.
Dependent Claims – Claims 2, 18 recite more abstract idea in apply it manner. See MPEP 2106.04(a)(2)(I)(A-C). Claim 3 recites more abstract idea. See MPEP 2106.04(a)(2)(II)(A-B). Claim 4 recites more abstract idea. See MPEP 2106.04(a)(2)(II)(A-B). Claim 5 recites more abstract idea. See MPEP 2106.04(a)(2)(II)(A-B). Claim 6 recites more abstract idea. See MPEP 2106.04(a)(2)(II)(A-B). Claim 7 recites more abstract idea. See MPEP 2106.04(a)(2)(II)(A-B). Claim 8, 19 recites more abstract idea. See MPEP 2106.04(a)(2)(II)(A-B). Claim 9 recites more abstract idea. See MPEP 2106.04(a)(2)(I). Claim 10 recites more abstract idea. See MPEP 2106.04(a)(2)(I). Claim 11 recites more abstract idea. See MPEP 2106.04(a)(2)(II)(A-B). Claim 12 recites more abstract idea. MPEP 2106.05 citing RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) (“Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract”). Claim 13 recites more abstract idea. MPEP 2106.05(a)(2)(I). Claim 14 recites more abstract idea. MPEP 2106.04(a)(2)(I). Claim 16 recites more abstract idea. See MPEP 2106.04(a)(2)(III) citing Electric Power Group. Accordingly, claims 1-14 and 16-20 are rejected under 35 USC 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-8 and 11-20 are rejected under 35 U.S.C. 103 as being unpatentable over US Pat Pub No 2022/0180281 to Walton, in view of Peng (9/4/2024). A swap-body vehicle routing problem considering fuel consumption management and multiple vehicle trips, Future Transportation (“Peng”).
With regard to claim 1, Walton discloses the claimed system for coordinating and controlling the movement of trailers by a fleet of vehicles within a logistics environment (Walton abstract, [0025-26] [0085] Figs. 1-2 etc.), comprising: a processor (Walton [0138]); and a memory (Walton [0006] storing data in memory of processor - The data can be stored and used by the scheduling processor. Such data can include AV yard truck missions related to tasks, the identity of available AV yard trucks, and/or performance estimates for AV yard trucks with respect to the tasks and control parameters. The scheduling processor can also assign costs to performance of tasks and optimize based upon costs. The costs can relate to transitions between predetermined tasks.) having instructions stored thereon that, when executed by the processor, cause the controller to:
receive a set of trailer transportation jobs, each trailer transportation job (Walton, Fig. 3 shows missions as inputs to assignment, also [0037] [0045-47] [0075] [0088]) comprising a temporal requirement defining conditions to be satisfied by a trailer or a vehicle at a location during a time interval (see e.g. Walton, Fig. 3, element 320, disposition of vehicles available at that time.);
encode the temporal requirement of each trailer transportation job as a set of constraints on one or more of vehicle motion dynamics, trailer motion dynamics, and energy consumption behavior using a metric temporal logic (MTL) specification (this does not occur under the claims BRI, see above where the examiner has applied art to the “or a vehicle at a location. . . .” instead of the temporal requirement);
solve a constrained optimization problem optimizing a cost function subject to the set of constraints and a set of vehicle operation constraints to generate a plan comprising one or more trailer assignments, vehicle trajectories, and charging actions, wherein the cost function includes a trailer motion cost and an energy consumption cost indicative of a total amount of energy of the fleet of trucks (see Walton [0033-35], [0100] [0113], tracking truck battery consumption per mission, it says power consumption can be a constraint or control parameter in planning. Walton does not disclose energy consumption in the cost function. See Peng, pg 1005-1007, The objective is to minimize the delivery cost Z , which includes the driver’s wage 1 Z , the use cost of the swap location 2 The objective is to minimize the delivery cost Z, which includes the driver’s wage Z1, the use cost of the swap location Z2, and the vehicle cost Z3. Vehicle cost is further divided into the fixed cost of renting the vehicle Z′ 3, the driving cost Z′′ 3 , and the variable fuel cost Z′′′ 3 , which differs between trucks and trailers. The driving cost pertains to fuel Z , and the vehicle cost 3 divided into the fixed cost of renting the vehicle ' 3 fuel cost Z . Vehicle cost is further Z , the driving cost '' 3 ''' 3 Z , and the variable consumption based on distance, irrespective of the load. Variable fuel cost is calculated based on both distance and load. Various internal and external factors, such as vehicle weight, driver behavior, road conditions, and environmental conditions, can affect fuel consumption [36–40]. The fuel consumption function proposed by Barth et al. [41] is used Z , which differs between trucks and trailers. The driving cost pertains to fuel consumption based on distance, irrespective of the load. Variable fuel cost is calculated based on both distance and load. Various internal and external factors, such as vehicle weight, driver behavior, road conditions, and environmental conditions, can affect fuel consumption [36–40]. The fuel consumption function proposed by Barth et al. [41] is used to calculate variable fuel consumption.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Walton’s truck/trailer assignment process to include the cost function(s) described in Peng (e.g. pg 1005, “Vehicle cost is further divided into the fixed cost of renting the vehicle Z′ 3, the driving cost Z′′ 3 , and the variable fuel cost Z′′′ 3 , which differs between trucks and trailers.” The advantage of this combination, as described in Peng pg 1005, is to minimize the delivery cost by taking all of the different variables into account so that they can be monitored, according for, and optimized for e.g. cost savings.); and
execute at least a portion of the plan within the logistics environment to control the movement of the trailers by the fleet of vehicles (see Walton element 360; [0022] [0025] [0055] [0081-82] Figs. 2-4).
With regard to claim 2, Walton further discloses the processor is configured to solve the constrained optimization problem over a receding planning horizon that is shorter than at least one of the temporal requirement of the set of trailer transportation jobs, and wherein the cost function includes a continuous satisfaction term that represents a degree of progress toward satisfaction of the set of trailer transportation tasks (e.g. Walton, [0064]; see also Peng, Fig. 2, showing the continuous satisfaction term
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See combination of Walton and Peng, above).
With regard to claim 3, Walton further discloses the continuous satisfaction term is defined by a percentage satisfaction term indicative of a percentage of satisfaction of the set of constraints and a proximity term indicative of a measure of proximity of the trailer to a target location associated with a temporal requirement of a trailer transportation job of the set of the trailer transportation jobs (see e.g. Walton Fig. 8).
With regard to claim 4, Walton further discloses where the measure of proximity is computed based on a shortest path distance between a current location of the trailer and the target location (see e.g. Walton Fig. 8, where the distances between locations are connected through straight lines, the fastest/shortest path of routing between the two locations).
With regard to claim 5, Walton further discloses where the processor is further configured to receive, post execution of the portion of the plan, updated system state information including an updated position and an updated energy level of at least one vehicle of the fleet of vehicles (see Walton [0073], [0020]).
With regard to claim 6, Walton discloses the processor is further configured to solve the constrained optimization problem over a successive planning horizon based on the updated system state information (e.g. Walton, [0064]; see also Peng, Fig. 2, showing the continuous successive satisfaction term
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See combination of Walton and Peng, above).
With regard to claim 7, Walton further discloses where the processor is further configured to update the set of trailer transportation jobs for the successive planning horizon by adding one or more newly received jobs, removing one or more fully executed trailer transportation jobs of the set of trailer transportation jobs, and retaining one or more partially executed tasks trailer transportation jobs of the set of trailer transportation jobs (Walton [0049] (i) charging missions are added as they are needed based on workload and status of the AV).
With regard to claim 8, Walton is silent regarding the cost function. See Peng at e.g. pg 1005 Vehicle cost is further divided into the fixed cost of renting the vehicle Z′ 3, the driving cost Z′′ 3 , and the variable fuel cost Z′′′ 3 , which differs between trucks and trailers. The driving cost pertains to fuel Z , and the vehicle cost 3 divided into the fixed cost of renting the vehicle ' 3 fuel cost Z . Vehicle cost is further Z , the driving cost '' 3 ''' 3 Z , and the variable consumption based on distance, irrespective of the load. Variable fuel cost is calculated based on both distance and load. Various internal and external factors, such as vehicle weight, driver behavior, road conditions, and environmental conditions, can affect fuel consumption [36–40]. The fuel consumption function proposed by Barth et al. [41] is used Z , which differs between trucks and trailers. The driving cost pertains to fuel consumption based on distance, irrespective of the load. Variable fuel cost is calculated based on both distance and load. Various internal and external factors, such as vehicle weight, driver behavior, road conditions, and environmental conditions, can affect fuel consumption [36–40]. See combination of Walton and Peng above.
With regard to claim 11, Walton further discloses the temporal requirement of each trailer transportation job is expressed using the MTL specification comprising one or a combination of a bounded eventually operator and a bounded always operator (The temporal requirement does not occur in claim 1, and therefore does not occur here.).
With regard to claim 12, Walton further discloses to encode the temporal requirement of each trailer transportation job, the processor is further configured to generate a Boolean variable corresponding to each MTL subformula at each discrete time step within a planning horizon (The temporal requirement does not occur in claim 1, and therefore does not occur here.).
With regard to claim 13, Walton further discloses the set of vehicle operation constraints includes one or more of: constraints on trailer flow conservation (see e.g. [0042]), constraints on vehicle flow conservation, vehicle energy constraints, constraints that avoid undesirable trailer behaviors, and a docking maneuver constraint.
With regard to claim 14, Walton further discloses the vehicle energy constraints capture an energy level of each vehicle of the fleet of vehicles, and wherein the docking maneuver constraint avoids one or more vehicles of the fleet of vehicles crossing a road and a docking station where a docking maneuver is being performed (does not occur under BRI).
With regard to claim 15, Walton further discloses the fleet of vehicles includes one or more autonomous vehicles, and wherein to execute at least the portion of the plan, the processor is further configured to:generate, based on the plan, one or more control commands to the one or more autonomous vehicles; and control the one or more autonomous vehicles according to the one or more control commands (e.g. [0006] [0007] [0022] etc.).
With regard to claim 16, Walton further discloses the fleet of vehicles includes one or more manual vehicles, wherein, to execute at least the portion of the plan, the processor is further configured to transmit the plan to auditory or visual interfaces of the one or more manual vehicles, wherein the plan is provided to drivers of the one or more manual vehicles through the auditory or visual interfaces, and wherein the one or more manual vehicles are controlled by their respective drivers according to the plan (e.g. [0023] etc. manual or automated).
Claim(s) 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Walton, Peng, in view of Karaman et al. (2008) Vehicle routing problem with metric temporal logic specifications. Proceedings of the 47th IEEE Conference on Decision and Control, Cancun, Mex. (“Karaman”).
With regard to claim 9, Walton further discloses the constrained optimization problem is a Mixed Integer Linear Programming (MILP) problem ([0076] MILP, [0113], [0114-128]), the MILP problem comprises:
a set of decision variables representing the trailer assignments (Walton e.g. [0112] defines the binary variable Ctwo, where its “work” includes moving one trailer from one spot to another spot (Walton [0037] [0046]) and the solver outputs tasks assigned to each truck ([0093-98]), the vehicle trajectories, and the charging actions over a receding planning horizon (the vehicle trajectories and charging actions did not occur in in the examiner’s claim 1 interpretation/application of art, and therefore they do not occur here.);
a set of linear constraints derived from the MTL specification, the vehicle motion dynamics, the trailer motion dynamics, and the energy consumption behavior (see Walton at [0076] and [0128]. Under the claim’s BRI the “derived from . . . .” language is not granted weight because these limitations did not occur under the examiner’s interpretation/application of art of claim 1, and therefore do not occur here. Nevertheless, see Karaman, pg 3956-3957, where Karaman identifies MTL as a way to state quantitative timing requirements in vehicle routing and reference-grounded reason for this specific modification. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Walton to include these features of Karaman in order to optimize vehicle routing problem by solving the problem to optimality. See Karaman, Abstract); and
the cost function comprising one or more terms selected from: the trailer motion cost (see Peng pg 1005 Variable fuel cost is calculated based on both distance and load. Combination above.), the energy consumption cost, and a continuous satisfaction term that represents a degree of progress toward satisfaction of the set of trailer transportation tasks.
With regard to claim 10, (Original) The system of claim 9, wherein the set of linear constraints comprises: constraints applied to the set of decision variables to enforce vehicle transition feasibility and battery energy updates over the receding planning horizon (Walton [0016]); and constraints applied to a set of auxiliary variables introduced to represent satisfaction of one or more subformulae of the MTL specification (Walton [0076]).
Conclusion
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/PETER LUDWIG/Primary Examiner, Art Unit 3627
1 Claim 15 is found to be eligible.
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