DETAILED ACTION
Claims 21-40 dated 07/11/2025 are being considered and are pending examination.
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 Arguments
There was NO argument presented from the applicant in regards to Prior Art Rejection beside stating that during interview the examiner agreed that it overcome the rejection. Upon further in-depth review of prior art and the amendments, the prior art D’Eramo in figure 9 and discussed in detail below in the rejection section teaches at least one route feature of the one or more route features comprises a feature describing stops associated with ingress or egress of the autonomous vehicle associated with the planned route. The seats are configured according to the exit and entering of the passengers.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION. —The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 21-40 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. In regards to Claim 21/29/37, the claim limitation “at least one route feature of the one or more route features comprises a feature describing stops associated with ingress or egress of the autonomous vehicle associated with the planned route” is not clear to the office. Its not clear whose ingress or egress is the claim being referred to and also the claim language seems to be vague by using words such as “describing” “associated”. The office recommends the applicant to use word that positively recite the claim limitations which the applicant is trying to claim. Secondly for the compact prosecution, the examiner is interpreting this limitation as passengers getting in and out of the vehicle.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 21-40 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by D’Eramo et al. (US11376992) and herein after will be referred as D’Eramo respectively.
Regarding Claim 21, D’Eramo teaches an autonomous vehicle (Col. 15 Line 1-5: “In some embodiment, the vehicle 108 can be an autonomous vehicle that can perform various actions including driving, navigating, and/or operating, with minimal and/or no interaction from a human driver. In an autonomous embodiment, the vehicle 108 can be configured to operate in one or more modes including, for example, a fully autonomous operational mode, a semi-autonomous operational mode, a park mode, and/or a sleep mode.”) comprising:
a plurality of seats (Fig 6);
one or more sensors (Col.31 Line 15-18: “For example, the vehicle computing system 112 can receive one or more sensor outputs from one or more sensors 114 (e.g., one or more cameras, radar, sonar, and/or pressure sensors) of the vehicle 108 that can be used to detect one or more objects in the vehicle cabin 150 of the vehicle 108. The vehicle computing system 112 can use the one or more sensor outputs to determine the disposition of objects in the vehicle (e.g., the amount of passengers and/or cargo in the vehicle 108 and/or the location of the one or more seats 152/154 in the vehicle 108)”);
and one or more processors configured to (Col. 13 Line 13-16: “The one or more computing devices of the operations computing system 104 can include one or more processors and one or more memory devices. “):
access service request data indicative of one or more features associated with a planned route of the autonomous vehicle (Fig 9 Step #908: “At 908, the method 900 can include determining one or more locations of the one or more seats in the vehicle based at least in part on the order in which the one or more passengers or cargo will enter and/or exit the vehicle. For example, the vehicle computing system 112 can determine that the one or more seats in the rear portion of the vehicle cabin 150 will be grouped to allow a first set of passengers easier access to the one or more seats 152/154 in the front portion of the vehicle cabin 150. The vehicle computing system 112 can then ungroup the one or more seats 152/154 in the rear of the vehicle so that a second set of passengers can sit in the seats located in the rear portion of the vehicle cabin 150. In some embodiments, determining one or more locations of the one or more seats in the vehicle based at least in part on the order in which the one or more passengers or cargo will enter and/or exit the vehicle can be performed as part of determining a configuration of the one or more seats based at least in part on the occupancy data and the one or more states of the vehicle as described in 806 of the method 800 that is depicted in FIG. 8”)
and an initial seat configuration of an interior of the autonomous vehicle, wherein the initial configuration comprises a layout for the plurality of seats (Col.29 Line 1-6: “In some embodiments, the occupancy data can include a number of the one or more seats that will be occupied (e.g., a number of the one or more seats that will be occupied by passengers and/or cargo). For example, the occupancy data can include a number of the one or more seats including the one or more seats 152/154 that will be occupied and/or a complementary value indicating the number of the one or more seats that will be available for use (e.g., available for passengers and/or articles of cargo).”);
and at least one route feature of the one or more route features comprises a feature describing stops associated with ingress or egress of the autonomous vehicle associated with the planned route (Fig 9 Step #908: “At 908, the method 900 can include determining one or more locations of the one or more seats in the vehicle based at least in part on the order in which the one or more passengers or cargo will enter and/or exit the vehicle. For example, the vehicle computing system 112 can determine that the one or more seats in the rear portion of the vehicle cabin 150 will be grouped to allow a first set of passengers easier access to the one or more seats 152/154 in the front portion of the vehicle cabin 150. The vehicle computing system 112 can then ungroup the one or more seats 152/154 in the rear of the vehicle so that a second set of passengers can sit in the seats located in the rear portion of the vehicle cabin 150. In some embodiments, determining one or more locations of the one or more seats in the vehicle based at least in part on the order in which the one or more passengers or cargo will enter and/or exit the vehicle can be performed as part of determining a configuration of the one or more seats based at least in part on the occupancy data and the one or more states of the vehicle as described in 806 of the method 800 that is depicted in FIG. 8”)
determine occupancy data based on an output from the one or more sensors, the occupancy data indicative of one or more passengers occupying the autonomous vehicle (Col.31 Line 20-24: “The vehicle computing system 112 can use the one or more sensor outputs to determine the disposition of objects in the vehicle (e.g., the amount of passengers and/or cargo in the vehicle 108 and/or the location of the one or more seats 152/154 in the vehicle 108)”).
and implement seat adjustment instructions configured to adjust: (i) the initial seat configuration of at least one of the plurality of seats of the autonomous vehicle and (ii) a cargo capacity of the autonomous vehicle, the seat adjustment instructions generated based on the occupancy data and the one or more route features of the planned route
(Col.10 Line 14-47: “In some embodiments, the vehicle configuration system can group at least one seat of the one or more seats to at least one other seat of the one or more seats based at least in part on the configuration. For example, the vehicle configuration system can generate one or more control signals and/or data based at least in part on the configuration. The one or more control signals and/or data can be used to activate one or more motors of the seat interface and/or the one or more seats that can cause a portion (e.g., three of six seats in a vehicle) of the one or more seats to fold a bottom seating area upwards and be grouped together (e.g., brought together) in a rear portion of the vehicle's interior. In some embodiments, the vehicle configuration system can determine that only the one or more seats that are not occupied will be grouped (e.g., not occupied by a passenger or an article of cargo). Furthermore, the vehicle configuration system can include one or more sensors that can detect the presence of an object (e.g., a passenger and/or an article of cargo) that blocks grouping of any seat of the one or more seats. For example, the motors of the one or more seats and/or seat interface can be configured to stop or reverse movement in a particular direction when any resistance to the movement in that direction is detected. By way of further example, the vehicle computing system can be configured not to adjust the configuration of the one or more seats when any passengers and/or cargo are present in the vehicle (e.g., the vehicle configuration system will only adjust the one or more seats when the vehicle is unoccupied or vacant); And also see Fig.9 Step #908: “At 908, the method 900 can include determining one or more locations of the one or more seats in the vehicle based at least in part on the order in which the one or more passengers or cargo will enter and/or exit the vehicle. For example, the vehicle computing system 112 can determine that the one or more seats in the rear portion of the vehicle cabin 150 will be grouped to allow a first set of passengers easier access to the one or more seats 152/154 in the front portion of the vehicle cabin 150. The vehicle computing system 112 can then ungroup the one or more seats 152/154 in the rear of the vehicle so that a second set of passengers can sit in the seats located in the rear portion of the vehicle cabin 150. In some embodiments, determining one or more locations of the one or more seats in the vehicle based at least in part on the order in which the one or more passengers or cargo will enter and/or exit the vehicle can be performed as part of determining a configuration of the one or more seats based at least in part on the occupancy data and the one or more states of the vehicle as described in 806 of the method 800 that is depicted in FIG. 8”).
Similarly Claims 29 and 37 are rejected.
Regarding Claim 22, D’Eramo teaches the autonomous vehicle of claim 21. D’Eramo also teaches wherein the one or more processors are further configured to determine a state of the one or more passengers occupying the autonomous vehicle (Col.3 Line 62-66: “The computing system can then perform operations associated with determining the state of the vehicle (e.g., how many passengers or articles of cargo are currently in the vehicle and/or where are the seats currently located).”).
Similarly Claims 30 and 38 are rejected.
Regarding Claim 23, D’Eramo teaches the autonomous vehicle of claim 22. D’Eramo also teaches wherein the state of the one or more passengers is indicative of a position and an orientation of respective passengers occupying the autonomous vehicle (Col.5 Line 5-20: “In some embodiments, the occupancy data can be associated with information including a number of passengers that will occupy the one or more seats, the assignment of one or more passengers to the one or more seats of the vehicle, and/or an amount of cargo that will occupy the vehicle. For example, the occupancy data can indicate that three passengers and two articles of cargo (e.g., two cubic boxes measuring half a meter per side and with a mass of twenty kilograms) will be entering the vehicle. Furthermore, the occupancy data can include one or more personal preferences of passengers including requested seating locations within the vehicle (e.g., window seats, seats towards the rear portion of the vehicle, and/or seats towards the front of the vehicle). By way of further example, the occupancy data can indicate the seats in which each of one or more passengers of the vehicle is assigned to be seated.”)).
Similarly Claims 31 and 39 are rejected.
Regarding Claim 24, D’Eramo teaches the autonomous vehicle of claim 21. D’Eramo also teaches wherein the occupancy data comprises data indicative of the autonomous vehicle being in one of an occupied mode or a non-occupied mode (Col. 5 Line 5-20: “In some embodiments, the occupancy data can be associated with information including a number of passengers that will occupy the one or more seats, the assignment of one or more passengers to the one or more seats of the vehicle, and/or an amount of cargo that will occupy the vehicle. For example, the occupancy data can indicate that three passengers and two articles of cargo (e.g., two cubic boxes measuring half a meter per side and with a mass of twenty kilograms) will be entering the vehicle. Furthermore, the occupancy data can include one or more personal preferences of passengers including requested seating locations within the vehicle (e.g., window seats, seats towards the rear portion of the vehicle, and/or seats towards the front of the vehicle). By way of further example, the occupancy data can indicate the seats in which each of one or more passengers of the vehicle is assigned to be seated.”).
Similarly Claims 32 and 40 are rejected.
Regarding Claim 25, D’Eramo teaches the autonomous vehicle of claim 24. D’Eramo also teaches wherein the occupied mode is associated with one or more seat adjustments that accommodate at least one of (i) the one or more passengers occupying the autonomous vehicle, or (ii) one or more objects occupying the autonomous vehicle (Col.5 Line 9-13“In some embodiments, the occupancy data can be associated with information including a number of passengers that will occupy the one or more seats, the assignment of one or more passengers to the one or more seats of the vehicle, and/or an amount of cargo that will occupy the vehicle. For example, the occupancy data can indicate that three passengers and two articles of cargo (e.g., two cubic boxes measuring half a meter per side and with a mass of twenty kilograms) will be entering the vehicle. Furthermore, the occupancy data can include one or more personal preferences of passengers including requested seating locations within the vehicle (e.g., window seats, seats towards the rear portion of the vehicle, and/or seats towards the front of the vehicle). By way of further example, the occupancy data can indicate the seats in which each of one or more passengers of the vehicle is assigned to be seated.”).
Similarly Claim 33 is rejected.
Regarding Claim 26, D’Eramo teaches the autonomous vehicle of claim 25. D’Eramo also teaches wherein the one or more processors are further configured to detect, using the one or more sensors, the one or more passengers and the one or more objects occupying the autonomous vehicle (Col.31 Line 20-32: “The vehicle computing system 112 can use the one or more sensor outputs to determine the disposition of objects in the vehicle (e.g., the amount of passengers and/or cargo in the vehicle 108 and/or the location of the one or more seats 152/154 in the vehicle 108). By way of further example, the vehicle computing system 112 can determine the location and/or position of the one or more seats 152/154 based at least in part on one or more control signals and/or or data indicating the disposition of the one or more seats 152/154 (e.g., the vehicle computing system 112 can poll the one or more seats 152/154 and, in response, receive data indicating the seat disposition from each of the one or more seats 152/154).”).
Similarly Claim 34 is rejected.
Regarding Claim 27, D’Eramo teaches the autonomous vehicle of claim 25. D’Eramo also teaches wherein the seat adjustment instructions adjust one or more seats unoccupied by the one or more passengers or the one or more objects (Col.36 Line 24-33: “At 1006, the method 1000 can include grouping the one or more seats that will not be occupied. For example, in a vehicle with four seats, when the occupancy data indicates that two seats of the one or more seats 152 will be occupied and that two seats of the one or more seats 152 will not be occupied, the vehicle computing system 112 can group the two seats that will not be occupied. In this way, by grouping two seats the two seated passengers of the vehicle 108 can enjoy a greater amount of free space around their respective seats.”).
Similarly Claim 35 is rejected.
Regarding Claim 28, D’Eramo teaches the autonomous vehicle of claim 25. D’Eramo also teaches wherein the seat adjustment instructions maintain the initial seat configuration for respective seats occupied by the one or more passengers or the one or more objects (Col. 10 Line 31-36: “By way of further example, the vehicle computing system can be configured not to adjust the configuration of the one or more seats when any passengers and/or cargo are present in the vehicle (e.g., the vehicle configuration system will only adjust the one or more seats when the vehicle is unoccupied or vacant)”).
Similarly Claim 36 is rejected.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDHESH K JHA whose telephone number is (571)272-6218. The examiner can normally be reached M-F:0800-1700.
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/ABDHESH K JHA/Primary Examiner, Art Unit 3668