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 .
Introduction
The following is a non-final Office action in response to Applicant’s RCE submission filed on 3/2/2026. Currently claims 1-17 are pending and claims 1, 10, 16 are independent. Claims 1, 10, 16, have been amended from the previous claim set dated 10/29/2025. No claims have been added or cancelled.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 3/2/2026 has been entered.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. JP2023-010836, filed on 1/27/2023.
Response to Amendments
Applicant’s amendments are acknowledged and necessitated the new grounds of rejection in this Office Action.
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 1-17 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), specifically an abstract idea, without significantly more. With respect to claims 1-17, following the guidance contained within MPEP 2106, the inquiry for patent eligibility follows two steps: Step 1: Does the claimed invention fall within one of the four statutory categories of invention? Step 2A (Prong 1): Is the claim “directed to” an abstract idea? Step 2A (Prong 2): Is the claim integrated into a practical application? Step 2B: Does the claim recite additional elements that amount to “significantly more” than the abstract idea?
In accordance with these steps, the Examiner finds the following:
Step 1: Claim 1 and its dependent claims (claims 2-9) are directed to a statutory category, namely a system/machine. Claim 10 and its dependent claims (claims 11-15) are directed to a statutory category, namely a method. Claim 16 and its dependent claims (claim 17) are directed to a statutory category, namely a system/machine.
Step 2A (Prong 1): Claims 1, 10, and 16, which are substantially similar claims to one another, are directed to the abstract idea of “Mental processes”, or more particularly, “Concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (See MPEP 2106).” In this application that refers to using a computer system to manage and analyze dispatching schedules for electric delivery vehicles. To clarify this further, the Applicant’s disclosed invention is a conceptual system meant to perform the same function that dispatcher might perform for a parcel delivery company. The abstract elements of claims 1, 10, and 16, recite in part “Generate schedule proposals…Evaluate proposals…Evaluate combinations…Select proposal…”. Dependent claims 2-9, 11-15, 17, add to the abstract idea the following limitations which recite in part “Evaluate each item…Add or change base point…Consider movement cost…Manage coefficient…Calculate value…Select combination…Display information…Transmit schedule…Display schedule…”. All of these additional limitations, however, only serve to further limit the abstract idea, and hence are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 10, and 16.
Step 2A (Prong 2): Independent claims 1, 10, and 16, which are substantially similar claims to one another, do not contain additional elements, either considered individually or in combination, that effectively integrate the exception into a practical application of the exception. These claims do include the limitation that recites in part “Schedule generation system…proposal unit…evaluation unit…Schedule generation apparatus……” which limits the claims to a networked/computer based environment, but this is insufficient with respect to integration into a practical application because it is merely applying the abstract idea to a general computer (See MPEP 2106.05(f)).
Dependent claims 6, 7, 8, 9 add the additional element which recites in part “Terminal…Display device…” which again limits the claims to a networked/computer based environment, but this is also insufficient with respect to integration into a practical application because it is again merely applying the abstract idea to a general computer (See MPEP 2106.05(f)).
Additionally, dependent claims 2-5, 11-15, 17 do not include any additional elements to conduct a further Step 2A (Prong 2) analysis.
Step 2B: Independent claims 1, 10, and 16, which are substantially similar claims to one another, include additional elements, when considered both individually and as an ordered combination, which are insufficient to amount to significantly more than the judicial exception. The additional elements of these claims recite in part “Schedule generation system…proposal unit…evaluation unit…Schedule generation apparatus …”. These items are not significantly more because these are merely the software and/or hardware components used to implement the abstract idea (manage and analyze dispatching schedules for electric delivery vehicles) on a general purpose computer (See MPEP 2106.05(f)). This is exemplified in the Applicant’s specification in P.8 – “The transportation schedule generation apparatus 2 is configured with a general-purpose computer apparatus that includes a central processing unit (CPU) 10...”
Dependent claims 6, 7, 8, 9 include additional elements, when considered both individually and as an ordered combination and in view of their respective independent claims, which are insufficient to amount to significantly more than the judicial exception. Specifically, dependent claims 6, 7, 8, 9 include the additional element which recites in part “Terminal…Display device …” These are similar additional elements that are addressed above in claims 1, 10, and 16, and are not significantly more because these are again merely the software and/or hardware components used to implement the abstract idea (manage and analyze dispatching schedules for electric delivery vehicles) on a general purpose computer (See MPEP 2106.05(f)).
Additionally, dependent claims 2-5, 11-15, 17 do not include any additional elements to conduct a further 2B analysis.
Accordingly, whether taken individually or as an ordered combination claims 1-17 are rejected under 35 USC § 101 because the claimed invention is directed to a judicial exception, an abstract idea, without significantly more.
Claim Rejections - 35 USC § 103
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, 2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 15, 16, 17 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (US 20240027199 A1) in view of Tang et al. (CN 111311158 B) further in view of Kim et al. (KR-20240077643-A)
Regarding claims 1, 10, and 16 (Amended), Kumar discloses a transportation schedule generation system that re- generates a pre-generated transportation schedule of loads by transportation vehicles which are motor vehicles (Kumar ABS - Aspects of the present disclosure provide methods, devices, and computer-readable storage media that support adaptive scheduling of electric vehicles (EVs) of an EV fleet for order deliveries), the system comprising: charging schedule proposals of the transportation vehicles based on the original transportation schedule and a remaining charging amount of each of the present transportation vehicles (Kumar ¶44 - In some examples, the intelligent charging parameter may indicate or may be used to determine an amount of charging to be performed for a vehicle for a particular delivery of the deliveries…Based on the order data 152, the adaptive EV scheduling engine 126 may determine an estimated charge consumption associated with the particular delivery (e.g., based on a travel distance associated with the particular delivery). Based on a difference between the SOC and the estimated charge consumption, the adaptive EV scheduling engine 126 may generate an indication of an amount of charging to be performed for the EV 182 at the charging station); and a schedule proposal evaluation unit configured to evaluate at least a delivery delay of the loads for each of the generated combinations of the transportation schedule proposals and the charging schedule proposals and select a combination of the transportation schedule proposal and the charging schedule proposal based on an evaluation result (Kumar ¶141 - Continuing with the above example, suppose that the dynamic scheduling determines there is a charging station that the first EV could use to charge its power source to a sufficient level to accommodate the new and existing deliveries. Under this scenario is may be ambiguous as to whether it is optimal to assign the new delivery to the first EV, which will need to visit a charging station to complete all deliveries, or the second EV, which will not need to charge to complete all deliveries. Using the multi-factored analysis described above, the dynamic scheduling may compute delay metrics for the first and second EVs to determine whether the new delivery will result in unsatisfactory delays in the remaining deliveries for the first and second EVs. Assuming the delay metrics for the first and second EVs both satisfy the threshold delay, the EV providing the more optimal delivery time (i.e., lowest delay metric) may be assigned the new delivery, resulting in an optimized scheduling of the new delivery and all existing deliveries) wherein the schedule proposal evaluation unit evaluates each evaluation item of the delivery delay of the load (Kumar ¶141 - Using the multi-factored analysis described above, the dynamic scheduling may compute delay metrics for the first and second EVs to determine whether the new delivery will result in unsatisfactory delays in the remaining deliveries for the first and second EVs), an operation time increase of the transportation vehicle (Kumar ¶7 - The adaptive EV scheduling engine may further receive vehicle data indicating vehicle parameters of the EV fleet, such as vehicle range, vehicle type, trailer size, battery status, utilization ratio {i.e. operation time increase} and maintenance schedule), and an operation time deviation of the transportation vehicle (Kumar ¶76 - In some examples, the vehicle classification and order provisioning engine 132 may determine the threshold based on one or more criteria. For example, the vehicle classification and order provisioning engine 132 may determine the threshold based on a load balancing scheme {i.e. operation time deviation}, such as where the threshold is selected to enable a distribution of work among EVs of the EV fleet 180); for each of the combinations of the transportation schedule proposals and the charging schedule proposals generated by the schedule proposal generation unit, overall evaluates the combinations based on an evaluation result of each evaluation item (Kumar ¶115 - One or more processes described herein may be performed iteratively. For example, a process associated with Equation 1 and Equation 2 may be performed during a first iteration for each vehicle associated with the EV fleet 180. After the first iteration, if one or more orders remain to be assigned, or if one or more vehicles of the EV fleet 180 are still available, the process may be performed again during a second iteration, etc.), and selects a combination of the transportation schedule proposal and the charging schedule proposal based on an overall evaluation result (Kumar ¶12 - The method further includes automatically generating, by the one or more processors, vehicle-to-order scheduling data based on the order data, the vehicle data, and one or more EV charging parameters associated with at least one EV of the plurality of EVs. The vehicle-to-order scheduling data indicates a mapping of the plurality of deliveries to the plurality of EVs).
Kumar lacks a schedule proposal generation unit configured to generate a plurality of combinations of transportation schedule proposals of the loads in which the loads to be transported are transported without the transportation vehicles running out of electricity.
Tang, from the same field of endeavor, teaches a schedule proposal generation unit configured to generate a plurality of combinations of transportation schedule proposals of the loads in which the loads to be transported are transported without the transportation vehicles running out of electricity (Tang ABS - S4, giving the vehicle number and the client number, generating all initial distribution solutions satisfying the constraint condition).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the EV scheduling methodology/system of Kumar by including the EV path planning techniques of Tang because Tang discloses “selecting the optimal distribution solution based on the target function (Tang)”. Additionally, Kumar further details “Aspects of the present disclosure provide methods, devices, and computer-readable storage media that support adaptive scheduling of electric vehicles (EVs) of an EV fleet for order deliveries (Kumar ABS)” so it would be obvious to consider including the additional EV path planning techniques that Tang discloses because it would create optimal solutions for Kumar to consider when scheduling EV delivery vehicles.
Kumar further lacks the operation time increase being a sum of times of the transportation vehicles that has increased when transportation is performed according to the transportation schedule proposal and the charging schedule proposal with respect to each transportation vehicle in the transportation schedule.
Kim, from the same field of endeavor, teaches the operation time increase being a sum of times of the transportation vehicles that has increased when transportation is performed according to the transportation schedule proposal and the charging schedule proposal with respect to each transportation vehicle in the transportation schedule (Kim Figs 8-10 – In addition, as seen in the embodiment of FIG. 8, the time required for the second vehicle 802, the fourth vehicle 804, and the seventh vehicle 807 to take delivery of the product allocated to the sixth vehicle 606 can increase. More specifically, the time required for unloading may be the later of the time required for loading and additional charging time. For example, the departure time for the second vehicle 802, the fourth vehicle 804, and the seventh vehicle 807 may be set to 1 hour 40 minutes, 2 hours 50 minutes, and 3 hours 20 minutes, respectively. The electronic device 100 may determine a charging schedule for charging a plurality of vehicles according to the embodiment of FIG. 8).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the EV scheduling methodology/system of Kumar by including the charging schedule techniques of Kim because Kim discloses “the electronic device 100 can more efficiently optimize the charging schedule of a plurality of vehicles (Kim)”. Additionally, Kumar further details “Aspects of the present disclosure provide methods, devices, and computer-readable storage media that support adaptive scheduling of electric vehicles (EVs) of an EV fleet for order deliveries (Kumar ABS)” so it would be obvious to consider including the additional charging schedule techniques that Kim discloses because it would improve the system of Kumar by optimizing the charging schedule of the EVs.
Regarding claim 2, 11, Kumar in view of Tang further in view of Kim discloses the schedule proposal evaluation unit evaluates each evaluation item of the delivery delay of the load (Kumar ¶141 - Using the multi-factored analysis described above, the dynamic scheduling may compute delay metrics for the first and second EVs to determine whether the new delivery will result in unsatisfactory delays in the remaining deliveries for the first and second EVs), an operation time increase of the transportation vehicle (Kumar ¶7 - The adaptive EV scheduling engine may further receive vehicle data indicating vehicle parameters of the EV fleet, such as vehicle range, vehicle type, trailer size, battery status, utilization ratio {i.e. operation time increase} and maintenance schedule), and an operation time deviation of the transportation vehicle (Kumar ¶76 - In some examples, the vehicle classification and order provisioning engine 132 may determine the threshold based on one or more criteria. For example, the vehicle classification and order provisioning engine 132 may determine the threshold based on a load balancing scheme {i.e. operation time deviation}, such as where the threshold is selected to enable a distribution of work among EVs of the EV fleet 180) for each of the combinations of the transportation schedule proposals and the charging schedule proposals generated by the schedule proposal generation unit, overall evaluates the combinations based on an evaluation result of each evaluation item, and selects a combination of the transportation schedule proposal and the charging schedule proposal based on an overall evaluation result (Kumar ¶12 - The method further includes automatically generating, by the one or more processors, vehicle-to-order scheduling data based on the order data, the vehicle data, and one or more EV charging parameters associated with at least one EV of the plurality of EVs. The vehicle-to-order scheduling data indicates a mapping of the plurality of deliveries to the plurality of EVs).
Regarding claim 3, 12, Kumar in view of Tang further in view of Kim discloses the schedule proposal generation unit adds or changes visit base points of the transportation vehicles and generates combinations of the transportation schedule proposals of the loads and the charging schedule proposals of the transportation vehicles in which the loads to be transported are all transported without the transportation vehicle running out of electricity (Kumar ¶138 - As another example, parameters of the order associated with the new delivery {i.e. add visit base point} may be used to perform dynamic scheduling. To illustrate, the order may include parameters that indicate a class of service or pickup time and the dynamic scheduling may determine whether the EV is capable of completing its existing deliveries and the new delivery within the constraints of the parameters of the order, such as after all existing deliveries are completed. In accounting for such order parameters the dynamic scheduling may also account for the charge level of the EV and availability of one or more charging stations (e.g., if the charge level is insufficient to accommodate the new delivery)).
Regarding claims 4, 13, Kumar in view of Tang further in view of Kim discloses the schedule proposal generation unit generates combinations of the transportation schedule proposals of the loads and the charging schedule proposals of the transportation vehicles considering a movement cost between the base points in addition to remaining charging amounts of the transportation vehicles (Kumar ¶123 - One or more features described herein may improve performance of a system, such as the system 100. For example, by planning dispatch operations based on the one or more charging parameters 120, energy expenditure associated with the deliveries 154 may be reduced, resulting in increased sustainability. To illustrate, assigning EVs of the EV fleet 180 to the deliveries 154 based on locations of charging stations (which may be indicated by the one or more charging parameters 120) may decrease an amount of time and distance traveled by an EV to a charging station, reducing road time, energy expenditure, and delivery latency in some instances. As a result, metrics such as cost and delivery time may be reduced while also reducing resource consumption (e.g., energy expenditure) and also increasing sustainability in the system 100).
Regarding claims 6, 15, Kumar in view of Tang further in view of Kim discloses a display device configured to display information, wherein the schedule proposal evaluation unit displays information regarding the selected combination of the transportation schedule proposal and the charging schedule proposal on the display device (Kumar ¶31 - In some implementations, the scheduling system 102 includes one or more input/output (I/O) devices that include one or more display devices, a keyboard, a stylus, one or more touchscreens, a mouse, a trackpad, a microphone, a camera, one or more speakers, haptic feedback devices, or other types of devices that enable a user to receive information from or provide information to the scheduling system 102. In some implementations, the scheduling system 102 is coupled to a display device, such as a monitor, a display (e.g., a liquid crystal display (LCD) or the like), a touch screen, a projector, a virtual reality (VR) display, an augmented reality (AR) display, an extended reality (XR) display, or the like. In some other implementations, the display device is included in or integrated in the scheduling system 102).
Regarding claim 7, Kumar in view of Tang further in view of Kim discloses information displayed on the display device includes an evaluation result of each of the evaluation items with regard to the combination of the transportation schedule proposal and the charging schedule proposal selected as the transportation schedule (Kumar ¶12 - The method further includes initiating transmission, by the one or more processors, of the vehicle-to-order scheduling data to initiate dispatch of the plurality of EVs for performance of the plurality of deliveries).
Regarding claim 9, Kumar in view of Tang further in view of Kim discloses a schedule management terminal installed at each base point at which collection or delivery of the loads or charging of the transportation vehicle is performed, wherein the schedule proposal evaluation unit transmits a job schedule of each base point included in the combination of the transportation schedule proposal and the charging schedule proposal selected as a new transportation schedule to the schedule management terminal of each corresponding base point, and each schedule management terminal displays the job schedule transmitted from the schedule proposal evaluation unit (Kumar ¶51 - The scheduling system 102 may transmit (e.g., via the one or more communication interfaces 110 {i.e. terminal}) the vehicle-to-order scheduling data 140 to initiate dispatch of at least some EVs of the EV fleet 180 for performance of the deliveries 154. To illustrate, the scheduling system 102 may transmit the vehicle-to-order scheduling data 140 to a vehicle storage facility to dispatch the at least some EVs of the EV fleet 180 to perform the deliveries 154, such as by dispatching the EVs to respective pickup locations (e.g., one or more warehouses or other locations) associated with the deliveries 154. Alternatively or in addition, in some cases, an EV may receive the vehicle-to-order scheduling data 140 while performing or returning from another delivery, while being charged, while being serviced according to a maintenance schedule, or based on another condition or event).
Regarding claim 17, Kumar in view of Tang further in view of Kim discloses wherein the supply schedule proposal is a schedule proposal including at least one of a schedule in which batteries of the transportation vehicles are charged and a schedule in which the batteries of the transportation vehicles are exchanged (Kumar ¶6 - For example, the adaptive EV scheduling may include identifying an energy efficient route that also reduces stress on a battery of an EV and may be based at least in part on one or more charging parameters associated with the EV. In some examples, the one or more charging parameters may include one or more of a state of charge (SOC) associated with the battery, a state of health (SOH) associated with the battery, a location of a charging station for the EV, an average charging duration associated with the EV, or an intelligent charging parameter associated with the EV (e.g., an amount of charging to be performed for the EV based on a particular order)).
Claims 5 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (US 20240027199 A1) in view of Tang et al. (CN 111311158 B) further in view of Kim et al. (KR-20240077643-A) further in view of JP 7194346 B2
Regarding claim 5, 14, Kumar in view of Tang further in view of Kim discloses a transportation schedule generation system that re- generates a pre-generated transportation schedule of loads by transportation vehicles which are motor vehicles (Kumar ABS - Aspects of the present disclosure provide methods, devices, and computer-readable storage media that support adaptive scheduling of electric vehicles (EVs) of an EV fleet for order deliveries).
Kumar in view of Tang further in view of Kim lacks wherein the schedule proposal generation unit manages a weight coefficient of each of the set evaluation items, calculates an evaluation value of each of the evaluation items with regard to each of the combinations of the transportation schedule proposals and the charging schedule proposals, and calculates, as an overall evaluation value, a total sum of multiplication results obtained by multiplying the evaluation values of the evaluation items by the corresponding weight coefficients, and selects a combination of the transportation schedule proposal and the charging schedule proposal based on the calculated overall evaluation value for each of the combinations of the transportation schedule proposals and the charging schedule proposals.
JP, from, the same field of endeavor, teaches wherein the schedule proposal generation unit manages a weight coefficient of each of the set evaluation items, calculates an evaluation value of each of the evaluation items with regard to each of the combinations of the transportation schedule proposals and the charging schedule proposals, and calculates, as an overall evaluation value, a total sum of multiplication results obtained by multiplying the evaluation values of the evaluation items by the corresponding weight coefficients, and selects a combination of the transportation schedule proposal and the charging schedule proposal based on the calculated overall evaluation value for each of the combinations of the transportation schedule proposals and the charging schedule proposals (JP - For example, the vehicle allocation process is executed in the following flow. (a) Vehicles that do not match the user information (luggage size, desired grade, etc.) are excluded from being dispatched to the user. (b) setting a weighting factor for the first priority according to the tentatively determined priority of the vehicle; (c) Set a second priority weighting factor according to the accumulated waiting time or the number of times of waiting on the day. (d) Determining high/medium/low power consumption (long/medium/short distance) in the user information by threshold, and determining high/medium/low remaining battery level of the vehicle with the highest priority by threshold. A weighting factor of the third priority is set from the vehicle whose class matches or is close to the class. (e) Multiply (or add) the respective coefficients to determine priority and assign the vehicle with the highest priority).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the EV scheduling methodology/system of Kumar by including the EV dispatch techniques of JP because JP discloses “improving the overall transport efficiency of electric vehicles and increasing the number of riders. This is advantageous for improving convenience (JP)”. Additionally, Kumar further details “Aspects of the present disclosure provide methods, devices, and computer-readable storage media that support adaptive scheduling of electric vehicles (EVs) of an EV fleet for order deliveries (Kumar ABS)” so it would be obvious to consider including the additional EV dispatch techniques that JP discloses because it would improve the efficiency of the EV delivery schedules disclosed within Kumar.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (US 20240027199 A1) in view of Tang et al. (CN 111311158 B) further in view of Kim et al. (KR-20240077643-A) further in view of Nishimura et al. (US 20210241626 A1)
Regarding claim 8, Kumar in view of Tang further in view of Kim discloses a transportation schedule generation system that re- generates a pre-generated transportation schedule of loads by transportation vehicles which are motor vehicles (Kumar ABS - Aspects of the present disclosure provide methods, devices, and computer-readable storage media that support adaptive scheduling of electric vehicles (EVs) of an EV fleet for order deliveries).
Kumar in view of Tang further in view of Kim lacks an in-vehicle terminal mounted in each of the transportation vehicles, wherein the schedule proposal evaluation unit transmits a transportation schedule of each of the transportation vehicles included in the selected combination of the transportation schedule proposal and the charging schedule proposal to the in-vehicle terminal of the corresponding transportation vehicle, and each of the in-vehicle terminals displays the transportation schedule transmitted from the schedule proposal evaluation unit.
Nishimura, from, the same field of endeavor, teaches an in-vehicle terminal mounted in each of the transportation vehicles, wherein the schedule proposal evaluation unit transmits a transportation schedule of each of the transportation vehicles included in the selected combination of the transportation schedule proposal and the charging schedule proposal to the in-vehicle terminal of the corresponding transportation vehicle, and each of the in-vehicle terminals displays the transportation schedule transmitted from the schedule proposal evaluation unit (Nishimura ¶101 - The on-vehicle device 4 of each vehicle 3 includes an input interface (not shown) that receives input of an operation of the driver. The input interface is composed of, for example, an input device attached to the navigation device, an input device of a data communication terminal mounted on the vehicle 3, or the like – Nishimura ¶4 - In the above vehicle dispatch system, when the center device receives a vehicle dispatch request from a user terminal, the center device determines a vehicle that can arrive at the riding position of the user earliest, as a dispatch vehicle, and transfers the vehicle dispatch request received from the user terminal, to an on-vehicle device of the determined dispatch vehicle).
It would be obvious for one of ordinary skill in the art before the effective filing date of the Applicant’s claimed invention to modify the EV scheduling methodology/system of Kumar by including the vehicle dispatch techniques of Nishimura because Nishimura discloses “an appropriate electric vehicle can be dispatched in accordance with the charging priority (Nishimura ¶21)”. Additionally, Kumar further details “Aspects of the present disclosure provide methods, devices, and computer-readable storage media that support adaptive scheduling of electric vehicles (EVs) of an EV fleet for order deliveries (Kumar ABS)” so it would be obvious to consider including the additional EV dispatch techniques that Nishimura discloses because it would improve the efficiency of the EV delivery schedules disclosed within Kumar by selecting the appropriate vehicle to dispatch.
Response to Arguments
Applicant's arguments filed 3/2/2026 have been fully considered but they are not persuasive and/or are moot in light of the new rejections addressed above.
Regarding the arguments related to the 35 USC § 101 rejections, as addressed above according to guidance for 35 USC § 101 rejections contained within MPEP 2106, the Examiner maintains that the claimed invention is an abstract idea, without significantly more, and not integrated into a practical application.
Applicant first argues that the claims are patent eligible because they are an improvement to a technology (Overcome rejection within the Step 2A (Prong 1) analysis). Examiner does not find this persuasive because the claims are interpreted as an improvement to an information gathering and analysis technique (e.g. how best to organize rides) that happens to take place by means of a computer.
The Applicant also argues as to how the claimed invention is further integrated into a practical application by addressing the optimized scheduling aspect of the claimed invention. While this optimized scheduling aspect might be an improvement to the delivery business, and as such, have practical applicability, this practical applicability is not synonymous with USPTO guidance. Specifically, the claimed invention needs have significant additional elements as to where the claimed invention is effectively integrated into those additional elements. As explained above, the additional elements “Schedule generation system…proposal unit…evaluation unit…Schedule generation apparatus…” limit the claims to a networked/computer based environment, but this is insufficient with respect to integration into a practical application because it is merely applying the abstract idea to a general computer (See MPEP 2106.05(f)).
Regarding the 35 USC § 103 rejections on the original Office action, Applicant amended the independent claims to further limit the claims with respect calculating time for each vehicle. In light of this amendment, Examiner agrees that the cited references did not clearly cite to this, however the amendment necessitated further search and consideration. As a result of this further search and consideration, prior art was found that does teach these limitations and is now cited (Kim as discussed above). As such, Applicant’s arguments (with respect to the independent claims and their respective dependent claims) are unpersuasive.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Yu et al. (JP 2023003163 A)
This prior art is cited because it discloses variations on scheduling deliveries using EVs and having multiple candidate options.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael R Koester whose telephone number is (313)446-4837. The examiner can normally be reached Monday thru Friday 8:00AM-5:00 PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached at (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MICHAEL R KOESTER/Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624
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