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 .
Response to Amendment
The amendment filed September 25, 2025 has been entered. Claims 1, 5-10, 14-18 remain pending in the application.
Response to Arguments
Applicant's arguments filed September 25, 2025 have been fully considered.
[1] Rejections under 35 U.S.C. §101
Applicant’s arguments that the amended claims overcome 35 U.S.C. §101 rejections are persuasive, and the rejections under 35 U.S.C. §101 are withdrawn.
[2] Rejections under 35 U.S.C. §103
Applicant argued that the cited references does not teach the amended limitations of the independent claims: "analyzing the call pattern by inputting the favorite list, the call history, and the list of idle autonomous vehicles into a pre-trained artificial intelligent model" and "wherein the favorite list includes ... the autonomous driving OS being an operating system that controls functions of the autonomous vehicle".
In this office action, Kwatra is cited to reject the limitation related to the artificial intelligent model. The limitation related to the autonomous driving OS is rejected citing the abstract, Fig. 3, paragraphs [0037], [0038] of Graney.
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.
Claim(s) 1, 5-10, 14-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hase et al. (JP2020077105A), which was cited by Applicant, in view of Kim (US 20200126000 A1), which was cited by Applicant, Kwatra et al. (US 20220148035 A1), and Graney (US 20180265094 A1). Ebrahimi Afrouzi et al. (US 20220066456 A1) is cited as an example teaching a pre-trained model.
Regarding claim 1, Hase discloses:
A personal transport system, comprising: a processor, a memory, and a communication device, wherein the processor executes a program stored in the memory to perform {paragraph [0063] of the English translation discloses a server for car allocation service} : receiving, by the processor, a request for a personal transportation service using an autonomous vehicle from a terminal of a user {[0024] discloses receiving a request for dispatch from a user via the user terminal 34. [0081] discloses an autonomous vehicle}; analyzing, by the processor, a call of the user for the autonomous vehicle {[0041] discloses analyzing information relating to the allocation request from the user}; and determining, by the processor, a recommended autonomous vehicle to provide the personal transportation service to the user based on the analysis result of the call {[0007] discloses recommending a specific taxi to provide the personal transportation},
wherein when the processor performs the analyzing the call, the processor performs: querying a list of idle autonomous vehicles around a call location of the user {[0041], [0037] discloses position information and idling status vehicle}.
Hase does not disclose:
[1] analyzing the call is analyzing a call pattern of the user for the autonomous vehicle.
[2] querying a user information database for a call history of the user.
[3] wherein the processor further performs: querying the user information database for a favorite list of the user for the autonomous vehicle, wherein the favorite list includes information on an autonomous vehicle preferred by the user.
[4] analyzing the call pattern by inputting the favorite list, the call history, and the list of idle autonomous vehicles into a pre-trained artificial intelligent model.
[5] the favorite list further includes information on an autonomous driving operating system (OS) for the autonomous vehicle preferred by the user, the autonomous driving OS being an operating system that controls functions of the autonomous vehicle.
[6] wherein information on a preferred autonomous vehicle and a preferred autonomous driving OS for the autonomous vehicle is input by the user to the user information database, and a predetermined number or fewer autonomous vehicles are managed by the user in the favorite list.
[1] – [3] Kim teaches to analyze call pattern of a user in [0009]: use history information related to each user… recommend a vehicle based on the vehicle use history information related to the user. [0072]: vehicle use history information related to the user, construed the favorite list. [0070]: The memory 320, construed the user information database, may store a vehicle use history of each user, function handling information related to each vehicle, and a similarity determination algorithm. The memory 320 may store vehicle sharing service subscriber information, vehicle sharing use registration information and/or vehicle information.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the user call pattern analysis feature of Kim with the described invention of Hase in order to determine a recommended autonomous vehicle based on history information of the calls of the user.
[4] Kwatra teaches artificial intelligence model for selection of autonomous vehicle in paragraph [0041]: machine-learning model can be used in order to understand and classify the relative state of the user and the activity of the user. Using a pre-trained artificial intelligent model is well known in prior art, for example, Ebrahimi Afrouzi et al. (US 20220066456 A1), paragraph [1186]: the classification algorithm described herein) may be pre-trained.
It would have been obvious to one of ordinary skill in the art l before the effective filing date of the claimed invention to incorporate the artificial intelligence model feature of Kwatra with the described invention of modified Hase in order to utilize artificial intelligence in analyzing user call pattern.
[5] Graney teaches an autonomous driving system, construed as autonomous driving operating system (OS) for the autonomous vehicle, in Fig. 3, [0037]: an autonomous driving system (ADS) as shown in FIG. 3. [0038]: autonomous driving system 70 can include a sensor fusion system 74, a positioning system 76, a guidance system 78, and a vehicle control system 80. As can be appreciated, in various embodiments, the instructions may be organized into any number of systems. Abstract: the user's preferences for the vehicle settings.
Examiner notes that page 9, lines 20-23 of the specification of the present application provides that an autonomous driving system is equivalent to an autonomous driving operating system.
It would have been obvious to one of ordinary skill in the art of vehicle control before the effective filing date of the claimed invention to incorporate the autonomous driving operating system feature of Graney with the described invention of modified Hase in order to consider user’s driving OS preference as a factor in recommending an autonomous vehicle according to the user call.
[6] Hase discloses user input in [0023]: Various processes are executed in response to operation input by a user. Examiner notes that managing to limit the number of preferred vehicles in the list is implied by the intended purpose of the invention because the number should not be too large in order to facilitate user selection.
It would have been obvious to one of ordinary skill in the art of vehicle control before the effective filing date of the claimed invention to modify the user input feature of Hase to limit the number of preferred vehicles in the list in order to facilitate producing the favorite list.
Similar reasoning applies to claim 10.
Regarding claim 5, which depends from claim 1, Hase discloses: wherein when the processor performs the receiving a request for a personal transportation service using an autonomous vehicle from a terminal of a user, the processor performs receiving a search request for an autonomous vehicle from the terminal, and wherein the search request includes at least one of a name, a size, a type, characteristics, a style, a shape, and a color of the autonomous vehicle {[0024] discloses selecting a vehicle to be assigned. [0037] discloses the type of the vehicle}.
Similar reasoning applies to claim 14.
Regarding claim 6, which depends from claim 5, Hase discloses: wherein the processor executes the program to further perform transmitting at least one available autonomous vehicle to the terminal in response to the search request, and wherein the at least one available autonomous vehicle is listed in an order of matching accuracy for search criteria of the user or in an order close to a current location or the calling location of the user {[0063] discloses assigning a taxi closest to the user location}.
Similar reasoning applies to claim 15.
Regarding claim 7, which depends from claim 1, Hase discloses: wherein the processor executes the program to further perform determining a waiting route for each autonomous vehicle based on the analysis result of the call pattern {[0029] discloses recommended travel plan for taxis based on the analysis result of the call pattern}.
Similar reasoning applies to claim 16.
Regarding claim 8, which depends from claim 7, Hase discloses: wherein the processor executes the program to further perform: receiving a request for the waiting route from an idle autonomous vehicle without a passenger and within which no call has been received; and transmitting the waiting route determined based on the analysis result of the call pattern to the idle autonomous vehicle {[0030] discloses receiving a request for the waiting route from an idle autonomous vehicle: when the state of the taxi changes to an empty state, a recommended driving plan for the taxi can be automatically set. [0033] and [0034] disclose determining and transmitting the waiting route}.
Similar reasoning applies to claim 17.
Regarding claim 9, which depends from claim 1, Hase discloses: wherein the recommended autonomous vehicle includes an idle autonomous vehicle with no passengers or a scheduled idle autonomous vehicle for which a passenger is about to disembark {[0037]: idling status of a taxi}.
Similar reasoning applies to claim 18.
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
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/C.P./Examiner, Art Unit 3661
/RUSSELL FREJD/Primary Examiner, Art Unit 3661