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 .
DETAILED ACTION
Status of Claims
The following is a Final Office Action in response to Applicant’s amendment received 09/08/2025.
In accordance with Applicant’s amendment, claims 1-2 and 5 are amended, claim 3 is canceled, and claims 6-8 are added as new claims. Claims 1-2 and 4-8 are currently pending.
Response to Amendment
Applicant’s amendment necessitated the new ground(s) of rejection set forth in this Office Action.
The amendment to the title filed on 09/08/2025 is entered and the objection to the Specification is withdrawn in response.
The 35 U.S.C. §102(a)(1) rejection of claims 1-2 and 4 is withdrawn in response to applicant’s amendment, however a new ground of rejection is applied to these claims under §103 in the instant office action.
The 35 U.S.C. §101 rejection of claims 1-5 is withdrawn in response to applicant’s amendment, which has been determined to integrate the judicial exception into a practical application.
Response to Arguments
Response to §102/§103 Arguments – Applicant’s arguments (Remarks at pgs. 8-9) concerning the §102/§103 rejections are primarily raised in support of the amendments to independent claim 1 (and similarly applicable to new claim 6), which are believed to fully addressed in the new ground of rejection set forth below under 35 USC §103.
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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 4, and 6-8 are rejected under 35 U.S.C. §103 as unpatentable over Sakurada et al. (US 2022/0044572, hereinafter “Sakurada”) in view of Ramot et al., US 2019/0311307, hereinafter “Ramot”) in view of Hasegawa et al. (US 2020/0241557, hereinafter “Hasegawa”).
Claims 1/6: Sakurada teaches an information processing apparatus comprising a controller (pars. 48-53, 61-66, and Figs. 5 and 9: information processing apparatus; server controller 12 can perform demand forecasting for a plurality of services), configured to:
forecast demand for each type of business in a predetermined area (Abstract, pars. 8-9, 80, 82, 84-85, and 88, and Fig. 4 and 7: server controller is configured to perform demand forecasting for a plurality of services [i.e., each type of business]; server controller 12 performs, with respect to each of the plurality of geographic areas [i.e., predetermined area], demand forecasting for services and determines, with respect to each of the plurality of geographic areas, an arrangement of a plurality of vehicles 20 based on a result of the demand forecasting for the services); and
determine a type of business in which mobile business should be operated in the predetermined area based on a forecast result of the demand for the each type of business in the predetermined area (pars. 7-9, 80, 85-85, and 88: e.g., perform demand forecasting for a plurality of services, determine the mode of the cabin of the specific vehicle [i.e., type of business] based on a result of the demand forecasting; geographic areas may include, for example, different administrative divisions, urban areas of different cities, or the like. In those cases, the server controller 12 performs, with respect to each of the plurality of geographic areas [i.e., predetermined areas], demand forecasting for services and determines, with respect to each of the plurality of geographic areas, an arrangement of a plurality of vehicles 20 based on a result of the demand forecasting for the services; based on the demand forecasting for the services, the vehicle dispatch system 1 can have more vehicles 20 on standby in the respective geographic areas so that the services that are likely to be requested can be provided);
receive…from a terminal device of a user (par. 55: As the user terminal 30, for example, a mobile information terminal, such as a smartphone, may be used’ The user terminal 30 can receive an input from the user through the input/output unit and display; user terminal 30 can communicate with the server 10 via the network 40 using the communication interface. The user terminal 30 may communicate with a vehicle 20 via the network);
identify a most appropriate location…; generate a control instruction based on the identified most appropriate location (pars. 75, 80, and 86: server 10 also instructs the vehicle 20 to provide the service; Based on the determined arrangement of the plurality of vehicles 20, the server controller 12 may instruct one or more vehicles 20 included in the plurality of vehicles 20 to travel to the corresponding geographic area [an identified most appropriate location]; server controller 12 instructs a vehicle 20 that needs to travel across geographic areas to travel);
wirelessly transmit, by a communication interface of the controller, the control instruction over a network (pars. 55, 75, 86, and Figs. 1 and 10: communication interface is configured with, for example, a wireless communication module compatible with a communication method for the network; server controller 12 instructs a vehicle 20 that needs to travel across geographic areas to travel, via the server communication interface 11 and the network); and
control an automatically movable vehicle to autonomously travel to the most appropriate location based on the control instruction (pars. 30, 80, and Fig. 10: controller 12 may instruct one or more vehicles 20 included in the plurality of vehicles 20 to travel to area in the plurality of geographic areas; driving system 23 may drive autonomously by cooperating with the location detector 24 and the sensor 25 under the control of the vehicle controller).
Sakurada does not teach:
receive a time period from a terminal device of a user;
identify a most appropriate location for operating the mobile business based on the received time period and information on distribution of people in the predetermined area.
Ramot teaches:
receive a time period from a terminal device of a user (par. 118: By way of example, the user may specify there will be 200 virtual passengers (or the number of virtual ride requests) over a period of two hours. In some embodiments, the user may specify in the input the number of virtual passengers (or the number of virtual ride requests) in a region in the geographical area. By way of example, as illustrated in FIG. 7, the user may specify in the input that there are 50 virtual passengers in region 741 and 100 virtual passengers in region 742 within a period of two hours; See also, par. 27: plurality of mobile communications devices 120A-120F may further include a plurality of user devices 120A-120C associated with user);
identify a most appropriate location for operating the mobile business based on the received time period … (pars. 118 and 131: scenario module 604 may determine there would be 300 ride requests in the geographical area in a period of two hours based on historical statistics of the ride requests around the same time point within the period of two hours; processor may obtain the ride requests at a time point of the simulation period. The processor may virtually assign the ridesharing vehicles available to the ride requests and determine the driving route for each of the assigned ridesharing vehicles).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sakurada with Ramot because the references are analogous since they are each directed to features for utilizing demand data for to improve operations of a mobile business, which is within Applicant’s field of endeavor of determining location of mobile business based on forecasted demand in a predetermined area, and because modifying the teachings of Sakurada to incorporate Ramot’s features for receiving time period information from a user device and identify a most appropriate location for operating the mobile business based thereon, as claimed, would serve the motivation to efficiently provide appropriate services to users (Sakurada at pars. 47 and 63; See also, Ramot at par. 87: e.g., pick up both users about the same time at substantially the same location, improving service efficiency); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Sakurada and Ramot do not explicitly teach:
identify a most appropriate location for operating the mobile business based on … information on distribution of people in the predetermined area.
Hasegawa teaches:
identify a most appropriate location for operating the mobile business based on … information on distribution of people in the predetermined area (pars. 68-70: e.g., business management unit 2022 determines spots (business spots) that the mobile shop vehicle 100 performs business based on the acquired demand data. In this example, the business management unit 2022 determines that the mobile shop vehicle 100 performs business at nodes B, C, D, E shown in FIG. 4; The demand data includes, for example, a market population, the number of persons (predicted number of visitors) expected to visit the mobile shop vehicle 100 as a mobile shop, and a ratio of the persons expected to purchase any commodity or service in each of the areas corresponding to the business spots).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sakurada/Ramot with Hasegawa because the references are analogous since they are each directed to features for utilizing demand data for to improve operations of a mobile business, which is within Applicant’s field of endeavor of determining location of mobile business based on forecasted demand in a predetermined area, and because modifying the teachings of Sakurada/Ramot to incorporate Hasegawa’s location identification based on distribution of people in an area, as claimed, would serve the motivation to efficiently provide appropriate services to users (Sakurada at pars. 47 and 63; See also, Ramot at par. 87: e.g., pick up both users about the same time at substantially the same location, improving service efficiency) and/or to meet demand of a large number of persons (Sakurada at par. 64); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 6 is directed to a system that includes an automatically movable being capable of autonomous movement and controller for performing substantially similar limitations as recited in claim 1 and discussed above. Sakurada, in view of Ramot/Hasegawa, teaches a system that includes an automatically movable being capable of autonomous movement and controller (Sakurada at pars. 2, 30, 48-53, 61-66, 80, and Figs. 5 and 9: e.g., vehicle dispatch system, a server, and a vehicle dispatch method; controller 12 may instruct one or more vehicles 20 included in the plurality of vehicles 20 to travel to area in the plurality of geographic areas; driving system 23 may drive autonomously by cooperating with the location detector 24 and the sensor 25 under the control of the vehicle controller), and claim 6 is therefore rejected using the same references and for substantially the same reasons as set forth above.
Claim 2: Sakurada further teaches a communication interface, wherein the controller is configured to, using the communication interface, transmit, to a terminal apparatus of an operator, a command signal giving a command to change a mode of the automatically movable vehicle according to the determined type of business (Abstract, pars. 7-9, 32, 34, 53, 65, and Fig. 7: instruct the specific vehicle to perform a mode change to the determined mode via the server communication interface; server controller 12 may instruct the specific vehicle 20A to perform a mode change to the determined mode via the server communication interface 11. The server controller 12 can change the mode of the specific vehicle 20A in advance based on the demand forecasting for the services; vehicle 20A that has been instructed to perform a mode change performs the mode change to a specified mode. The mode change of the specific vehicle 20A may be performed automatically by the vehicle controller 22 in response to an instruction from the server controller 12, or may be at least partially performed manually; vehicle 20 that is used for autonomous driving).
Claim 4: Sakurada further teaches wherein the controller is configured to determine a type of business in which mobile business should be operated in the predetermined area by time period in a day based on a forecast result of demand for the each type of business in the predetermined area by time period in the day (pars. 58-59, 67, and Fig. 8: e.g., server controller 12 of the server 10 performs the demand forecasting for the respective services that can be provided by the vehicles 20 (Step S101). For example, the demand forecasting may be performed by considering date and time information for targets of the forecasting, weather information, and/or event holding information, as factors (hereinafter, also referred to as affecting factors) that affect the demand forecasting. The date and time information may include a time of the day, a day of the week, a date (month and day), a season, and the like; allows the server 10 to forecast what services will be demanded in various time periods and dispatch more vehicles 20 that can provide the forecasted services. For example, the server 10 may allocate more vehicles 20 that can provide the passenger transport service between 7:00 and 9:00 and between 16:00 and 18:00 for drop-off and pick-up of office and school commuter).
Claim 7: Sakurada further teaches wherein the controller is further configured to receive information from the terminal device of the user indicating a type of business to be conducted using the mobile object (Abstract, pars. 7-9, 32, 34, 47, 53, 65, and Fig. 7: accept various service provision requests transmitted from a plurality of user terminals 30 and dispatch vehicles 20 that are capable of providing requested services [i.e., type of business] to the users. The server 10 may instruct a specific vehicle 20A to perform a mode change at an appropriate time so as to efficiently provide appropriate services to users; instruct the specific vehicle to perform a mode change to the determined mode via the server communication interface).
Claim 8: Sakurada does not explicitly teach the limitation of claim 8.
However, Ramot further teaches wherein the controller is further configured to identify the most appropriate location further based on the received information (pars. 118 and 131: e.g., user may specify there will be 200 virtual passengers (or the number of virtual ride requests) over a period of two hours [received information]. In some embodiments, the user may specify in the input the number of virtual passengers (or the number of virtual ride requests) in a region in the geographical area [received information]; scenario module 604 may determine there would be 300 ride requests in the geographical area in a period of two hours based on historical statistics of the ride requests around the same time point within the period of two hours; processor may obtain the ride requests at a time point of the simulation period. The processor may virtually assign the ridesharing vehicles available to the ride requests and determine the driving route for each of the assigned ridesharing vehicles [identified most appropriate location]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further include, in the combination of Sakurada/Ramot/Hasegawa, Ramot’s identification of a most appropriate location based on received information, as claimed, in order to serve the motivation to efficiently provide appropriate services to users (Sakurada at pars. 47 and 63) so that usage efficiency can be maximized across geographic areas (Sakurada at par. 85); and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 5 is rejected under 35 U.S.C. §103 as unpatentable over Sakurada et al. (US 2022/0044572, hereinafter “Sakurada”) in view of Ramot et al., US 2019/0311307, hereinafter “Ramot”) in view of Hasegawa et al. (US 2020/0241557, hereinafter “Hasegawa”), as applied to claim 1 above, and further in view of Saleh (US 2020/0160718).
Claim 5: Sakurada does not teach the limitation of claim 5.
Saleh teaches wherein the controller is configured to determine a rental fee for the automatically movable vehicle in the predetermined area based on the forecast result of the demand for the each type of business in the predetermined area (pars. 18 and 45: The vehicle 200 may be an autonomous vehicle or a non-autonomous vehicle; When a ride share demand is predicted to increase, the computing device may adjust a ride share pricing (e.g., the price per ride is increased) for the geographic location based on the predicted demand in ride sharing requests, at block 340. For example, referring to the above football game example, because an increase in demand is predicted since there may not be sufficient vehicles available due to concurring events and traffic congestion).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Sakurada/Ramot/Hasegawa with Saleh because the references are analogous since they are each directed to features for utilizing demand data for to improve operations of a mobile business, which is within Applicant’s field of endeavor of determining location of mobile business based on forecasted demand in a predetermined area, and because modifying the teachings of Sakurada/Ramot/Hasegawa to incorporate Saleh’s demand based fees for transportation services in an area, as claimed, would serve the motivation to employ demand based pricing features (i.e., “surge pricing”) to maximize profits and balance supply with demand via dynamic pricing strategies; and further obvious because the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Farrelly et al. (US 2015/0262430): discloses determining a rental fee for a mobile object in a predetermined area based on a forecast result of the demand for a type of business in the predetermined area (pars. 14, 41, and 50).
Ferguson et al. (US 2019/0034858): discloses an information processing apparatus comprising a controller (pars. -65, 98-99, 106-110, 160, and Figs. 13-15: digital processing device; controllers and processors; one or more processors), configured to: forecast demand for each type of business in a predetermined area (pars. 8, 19, 63, and 79: anticipate demand for autonomous or semi-autonomous vehicle services [wherein autonomous is one type, semi-autonomous is another type] by storing data relating to the quantity, timing, and type of orders received in each region [i.e., a predetermined area]. Such demand prediction can be performed for both source location (e.g., restaurants, grocery stores, general businesses, etc.) and delivery location (e.g., customer, other businesses, etc.). Such demand predictions can further be weighted by the cost or importance of the good or service and employ historical trends for higher efficiency and throughput); and determine a type of business in which mobile business should be operated in the predetermined area based on a forecast result of the demand for the each type of business in the predetermined area (pars. 8, 19, 63, and 79: plurality of securable compartments are variably configurable based on: anticipated demands; patterns of behaviors; area of service [i.e., predetermined area]; or types of goods to be transported [i.e., type of business]; self-positioning of the autonomous or semi-autonomous vehicle fleet based on anticipated demand; autonomous fleet 100 is strategically positioned throughout a geographic region in anticipation of a known demand. Over time, a user 200 and/or a vendor 204 can anticipate demand for autonomous or semi-autonomous vehicle services [wherein autonomous is one type, semi-autonomous is another type] by storing data relating to the quantity, timing, and type of orders received in each region. Such demand prediction can be performed for both source location (e.g., restaurants, grocery stores, general businesses, etc.) and delivery location (e.g., customer, other businesses, etc.); In some embodiments, the plurality of securable compartments [which is indicative as to type of business] can be configured and reconfigured based on: anticipated demands, patterns of behaviors, area of service, the types of goods [i.e., which is indicative of a type of business]).
A. Petrovsky et al., "Customer behavior analytics using an autonomous robotics-based system," 2020 16th International Conference on Control, Automation, Robotics and Vision (ICARCV), Shenzhen, China, 2020, pp. 327-332: discloses automated technology such as mobile robots to monitor, e.g., product demand, in a retail environment, such as for aiding with crowd predictions at certain times of the day and to aid with predictions that maximize profit.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Timothy A. Padot whose telephone number is 571.270.1252. The Examiner can normally be reached on Monday-Friday, 8:30 - 5:30. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Brian Epstein can be reached at 571.270.5389. The fax phone number for the organization where this application or proceeding is assigned is 571- 273-8300.
Information regarding the status of an application may be obtained from Patent Center. Status information for published applications may be obtained from Patent Center. Status information for unpublished applications is available through Patent Center for authorized users only. Should you have questions about access to Patent Center, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form.
/TIMOTHY PADOT/
Primary Examiner, Art Unit 3625
10/01/2025