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 .
Claim Objections
Claims 6, 7 are objected to because of the following informalities: As to claims 6, 7 they are dependent on claim 5 which has been cancelled. Appropriate correction is required.
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.
Claims 1-3, 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over Yasui (US 2021/0146955) in view of Zender (US 2020/0182635)
As to claim 1 Yasui discloses an information processing apparatus comprising a controller, the controller comprising at least one processor and a memory storing non-transitory executable instruction, the processor configured to execute the instructions to execute:
acquiring from a sensor first data about behavior of an occupant of a first vehicle during a first period from when the first vehicle leaves a point of departure until the first vehicle reaches a first point (Paragraph 64 “The occupant monitor 130 may acquire a detection result of the extent of stress acquired by a biological sensor fixed to the body of the occupant through wireless communication or the like and may estimate the extent of stress on the occupant according to the acquired detection result of the biological sensor. The occupant monitor 130 may integrate the detection result of the biological sensor and the analysis result of the image captured by the vehicle interior camera 82 and may estimate the extent of stress on the occupant.” , 75 “When the acquired route includes a section in which the extent of stress is predicted to increase to be equal to or greater than the predetermined extent, the predictor 124 determines whether the section in which the extent of stress is predicted to increase can be avoided (step S104).”); and
providing driver assistance processing during a second period from when the first vehicle leaves the first point until the first vehicle reaches a destination (Paragraph 76 “hen the section in which the extent of stress is predicted to increase to be equal to or greater than the predetermined extent can be avoided, the automated driving controller 100 controls the vehicle M such that the vehicle M travels along the route in which the section in which the extent of stress is predicted to increase to be equal to or greater than the predetermined extent can be avoided (step S106). That is, the automated driving controller 100 controls the vehicle M such that the vehicle M preferentially travels in a section (route) different from the section (specific route) in which the extent of stress is predicted to increase to be equal to or greater than the predetermined extent. The route in which the section in which the extent of stress is predicted to increase to be equal to or greater than the predetermined extent is avoided is, for example, the most efficient route among the newly generated routes determined not to be inefficient.”).
Yasui does not explicitly disclose estimating at the first point, one or more first actions that are actions to be taken by the occupant at the second point based on waypoint that is information indicating a waypoint of the first vehicle;
Zender teaches estimating at the first point, one or more first actions that are actions to be taken by the occupant at the second point based on waypoint that is information indicating a waypoint of the first vehicle; (Paragraph 21 “The systems and methods disclosed herein allow a driver to plan stop-overs (waypoints) at the beginning of a trip or after the driver has started the trip using smart personalized search algorithms for finding optimal waypoints. During the trip, the system can perform context-aware monitoring that can add or adjust waypoints in response to changing circumstances. The waypoint adjustment can be triggered not only by user requests (e.g., verbal or haptic interaction), but also by signals from in-car sensors (e.g., low fuel/battery detection, drowsiness detection). The waypoint adjustment can be performed whether there is a navigation route being followed by the driver, or when no route guidance is currently active.”)
calculating a degree of fatigue of the occupant resulting from the first action after passing the second point (Paragraph 24 “Alternatively, or in addition to fuel level, the vehicle interface 110 can be configured to determine information regarding a drowsiness level of the driver, which the system 100 can use to determine and suggest waypoints for the driver”), and
determining, in advance, a content of a second driving support processing that is driving support processing to be executed in a third period from leaving the second point to reaching the third point based on the degree of fatigue (Paragraph 35 “Determining whether a candidate waypoint is reachable can be based on an amount of fuel remaining in the vehicle, level of driver drowsiness, or whether an establishment at the candidate waypoint is open at an estimated time of arrival at the candidate waypoint. The method 300 further includes determining 315 scores for candidate waypoints remaining in the set of candidate waypoints based on driver preference factors, and presenting 320 at least one candidate waypoint to the driver based on the scores for the candidate waypoints.”).
It would have been obvious to one of ordinary skill to modify Yasui to include the teachings of deciding a waypoint of the vehicle for the purpose of routing the vehicle based on the state of the user.
As to claim 2 Yasui discloses an information processing apparatus wherein the controller decides a driving environment for the first vehicle during the second period, based on the first data, and transmits data specifying the decided driving environment to a platform of the first vehicle (Paragraph 69).
As to claim 3 Yasui discloses an information processing apparatus wherein the controller decides parameters for an advanced driver assistance system (ADAS) of the first vehicle during the second period, based on the first data, and applies the decided parameters to the ADAS (Paragraph 76).
As to claim 21 Zender teaches an information processing apparatus wherein the controller executes:
acquiring support information that is information indicating content of the driving support processing defined for each degree of fatigue (Paragraph 35),
determining a content of the second driving support processing based on the degree of fatigue and the support information (Paragraph 35).
As to claim 22 the claim is interpreted and rejected as in claim 21.
Claims 8-10, 12-20 are rejected under 35 U.S.C. 103 as being unpatentable over Yasui (US 2021/0146955) in view of Zender (US 2020/0182635) as applied to claim 1 above, and in further view of Galm (US 2019/0223773)
As to claim 8 Galm teaches an information processing apparatus wherein the controller calculates an evaluation value indicating an amount of activity of the occupant during the first period, based on the first data (Paragraph 42). It would have been obvious to one of ordinary skill to modify Yasui to include the teachings of determining an amount of activity of the occupant for the purpose of routing the vehicle based on the state of the user.
As to claim 9 Galm teaches an information processing apparatus wherein the controller calculates the evaluation value further based on activity amount information acquired from a mobile terminal associated with the occupant(Paragraph 42).
As to claim 10 Galm teaches an information processing apparatus wherein the activity amount information includes at least either the number of steps or a distance of movement on foot (Paragraph 51).
As to claim 12 Galm teaches an information processing apparatus wherein the controller decides content of the driver assistance during the second period so that, the larger the amount of activity indicated by the evaluation value is, the smaller a load on the occupant during the second period is(Paragraph 89-90).
As to claim 13 Galm teaches an information processing apparatus wherein when the amount of activity indicated by the evaluation value exceeds a predetermined value, the controller changes a scheduled route of the first vehicle during the second period to a second scheduled route with a smaller load on the occupant(Paragraph 89-90).
As to claim 14 Galm teaches an information processing apparatus wherein the second scheduled route is a route including one or more break places decided based on the amount of activity indicated by the evaluation value(Paragraph 89-90).
As to claim 15 Galm teaches an information processing apparatus wherein the controller decides a driving position of the occupant during the second period, based on the amount of activity indicated by the evaluation value(Paragraph 89-90).
As to claim 16 Galm teaches an information processing apparatus wherein the controller decides parameters of an advanced driver assistance system (ADAS) of the first vehicle during the second period, based on the amount of activity indicated by the evaluation value(Paragraph 87).
As to claim 17 the claim is interpreted and rejected as in claim 1 and 9.
As to claim 18 the claim is interpreted and rejected as in claim 9.
As to claim 19 the claim is interpreted and rejected as in claim 10.
As to claim 20 the claim is interpreted and rejected as in claim 12.
Claims 6-7 are rejected under 35 U.S.C. 103 as being unpatentable over Yasui (US 2021/0146955) in view of Zender (US 2020/0182635) as applied to claim 1 above, and in further view of Kam (US 2020/0104323)
As to claim 6 Kam teaches an information processing apparatus wherein the controller judges an attribute of the first waypoint based on facility data, and estimates the behavior of the occupant based on the judged attribute(Paragraph 325-334)). It would have been obvious to one of ordinary skill to modify Yasui to include the teachings of determining an attribute of the waypoint based on the facility day for the purpose of categorizing the activity data of the user.
As to claim 7 Kam teaches an information processing apparatus wherein the controller estimates the behavior of the occupant further based on a stay time at the first waypoint(Paragraph 325-334)
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Yasui (US 2021/0146955) in view of Zender (US 2020/0182635) , and Galm (US 2019/0223773) as applied to claim 8 above, and in further view of Kam (US 2020/0104323)
As to claim 11 Kam teaches an information processing apparatus wherein the controller calculates the evaluation value further based on an utterance of the occupant detected in the first vehicle (Paragraph 191). IT would have been obvious to one of ordinary skill to modify Yasui to include the teachings of calculating an evaluation value for the purpose of detecting the drowsiness level of the occupant.
Response to Arguments
Applicant’s arguments with respect to claims 1, 3, 6-22 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IMRAN K MUSTAFA whose telephone number is (571)270-1471. The examiner can normally be reached Mon-Fri 9-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, James J Lee can be reached at 571-270-5965. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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IMRAN K. MUSTAFA
Primary Examiner
Art Unit 3668
/IMRAN K MUSTAFA/ Primary Examiner, Art Unit 3668
9/29/2025