DETAILED ACTION
This Final Office action is in response to Applicant’s Amendment on 03/11/2026. Claims 1, 3-10, 12-20 are pending. The effective filing date of the claimed invention is 11/17/2023.
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 Rejections - 35 USC § 102
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 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 1, 3-6, 8, 10, 12-15, 17, 19 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Shukla, Kathan, "AUTOMATIC RESERVATION SYSTEM FOR SMART CARS", Technical Disclosure Commons, (July 10, 2019)https://www.tdcommons.org/dpubs_series/2331 (referring to as “Shukla”).
With regard to claims 1, 10, and 19, Shukla discloses the claimed vehicle system (page 2-3, vehicle system) comprising:
a telematics control unit including a transceiver and configured to communicate with a restaurant (see page 6, “For example, computing device A may be an automobile infotainment system comprising a camera and computing device N may be a mobile phone (e.g., smart phone) comprising a camera.”);
one or more processors and a memory storing instructions executable by the one or more processors to cause the one or more processors (see e.g. page 2-3, “An interactive assistant, such as shown in the example of Figure 1 below, may be included in a computing system that is configured to interact with one or more users. The computing system may be, include, or otherwise be included in a mobile device (e.g., smart phone, tablet computer, laptop computer, computerized watch, computerized eyewear, computerized gloves), a personal computer, a smart television, a personal digital assistant, a portable gaming system, a media player, a mobile television platform, an automobile navigation and/or entertainment system, a vehicle (e.g., automobile, aircraft, navigable watercraft) and/or cockpit display, a home or other smart appliance and/or related device (e.g., interconnectable appliance/device via Internet of Things), or any other type of wearable, non-wearable, mobile, or non-mobile computing device, and the computing system may or may not include a display device. In some cases, the interactive assistant may be a voice-assistant that receives audible user commands, processes the commands based on speech recognition operations, and performs corresponding actions, such as providing audible responses to user queries and/or performing certain actions. The interactive assistant may provide or utilize a user interface with which a user can communicate to cause the assistant to output useful information, respond to a user’s queries, or otherwise perform certain operations to help the user complete a variety of real-world or virtual tasks.”):
detect a number of passengers in a vehicle using an image of a passenger cabin of the vehicle, and identify at least one passenger from among the passengers (e.g. page 2, “The assistant accesses a video stream from an electronic device and performs image recognition analysis to identify a number of people within a proximity of the electronic device.”; page 3, “The interactive assistant may, upon a user selecting a destination within a navigation application, access a video stream, for example, from a computing device, such as an in-car, or smart device, camera, identify a number of people that are within a proximity of the user (e.g., number of people within an automobile”; page 7-8 “The image analysis may also identify whether there are any children in the automobile by identifying a child car seat or child toys.” “The assistant may then perform image recognition analysis on the accessed video stream.”; abstract, “The assistant further, based on the image recognition analysis, may determine whether there are any people in the car who may require special accommodations (e.g., handicap accessibility, booster seats, highchairs, etc.).”; page 8 line 4-11);
determine whether the at least one passenger is dinein or pick-up food1 based on input from passenger (see throughout, determination of dinein based on user input at vehicle system, where user places a reservation for table/spot at restaurant, including the amount of people and time – “Figure 1 below illustrates an example of an interactive assistant that may generate a reservation request and then send the generated reservation request to a business (e.g., a restaurant, hotel, museum, or the like) or to a box office or digital reservation system for an event (e.g., an art gallery, play, concert, or the like), and then send the generated request to the, e.g., restaurant. The interactive assistant may, upon a user selecting a destination within a navigation application, access a video stream, for example, from a computing device, such as an in-car, or smart device, camera, identify a number of people that are within a proximity of the user (e.g., number of people within an automobile or a number of people walking with the user, such as within an area surrounding the user), generate a reservation request, and then send the reservation request to the user selected destination. For example, the reservation request may be sent to a host or hostess or made online through an online reservation system utilized by the restaurant.” e.g. page 2, “Prior to making the reservation, the assistant may prompt the user to confirm that the user would like to make the reservation.”, see abstract further where based on the input and image recognition, the system determines that special accommodations are needed, such as by identifying a toddler, and then indicating in the prompt to vehicle and in the reservation that “booster seats, [and/or] high chairs, etc.” are needed, where this is an indication of dining in; a further indication is making a reservation for a certain amount of people is an indication of dining in.)
establish using the telematics control unit a communication link with a computing device associated with the restaurant that is identified to be visited by the at least one passenger (e.g. page 3, “The interactive assistant may, upon a user selecting a destination within a navigation application, . . . generate a reservation request, and then send the reservation request to the user selected destination. For example, the reservation request may be sent to a host or hostess or made online through an online reservation system utilized by the restaurant.”);
transmit one of: a reservation message (see e.g. page 3, above) to schedule a reservation at the restaurant in response to determining that the at least one passenger is to dinein, the reservation including a number of people based on the number of passengers detected and a reservation time based on an arrival time to the restaurant, wherein the arrival time is based on an estimated travel time of the vehicle (see page 5, navigation application to determine ETA), an estimated parking time, and an estimated walking time to the restaurant (see e.g. abstract, “The assistant may then generate and then send a reservation request to the user-selected location for the arrival time for the number of identified people and any special accommodations that may be needed.”; page 9, “the assistant may add a margin for error to the time of arrival, such as five minutes allocated for the user to find parking and/or to walk from the parking lot to the selected destination. This may be done by locating any parking garages within a block or few blocks of the destination, and then by calculating the time to find the garage (by adding in a couple minutes) and to walk from the garage to the destination.”), or place, in response to detecting that the at least one passenger is picking-up food from the restaurant, a carryout order at the restaurant for the at least one passenger when a preparation time of the carryout order, received by the restaurant, is greater than or equal to the estimated travel time of the vehicle.
With regard to claims 3 and 12, Shukla further discloses estimating, by the vehicle system, the arrival time based on an estimated travel time of the vehicle, an estimated parking time, and an estimated walking time to the restaurant (see e.g. abstract, “The assistant may then generate and then send a reservation request to the user-selected location for the arrival time for the number of identified people and any special accommodations that may be needed.”; page 9, “the assistant may add a margin for error to the time of arrival, such as five minutes allocated for the user to find parking and/or to walk from the parking lot to the selected destination. This may be done by locating any parking garages within a block or few blocks of the destination, and then by calculating the time to find the garage (by adding in a couple minutes) and to walk from the garage to the destination.”).
With regard to claims 4 and 13, Shukla further discloses transmitting by the vehicle system a preparation message to obtain a preparation time for the carryout order in response to determining that the at least one passenger is to pickup the food (The pickup food order is not granted patentable weight as this is an “or” limitation that does not happen under the claims’ BRI); and estimating, by the vehicle system, a travel time of the vehicle to the restaurant, wherein the message is transmitted to place the carryout order when the preparation time of the carryout order is greater than or equal to the travel time of the vehicle (carryout out doesn’t happen, and therefore not granted patentable weight under BRI).
With regard to claims 5 and 14, Shukla discloses claim 1. Shukla was applied to the schedule reservation part of the “or” statement, not the carryout part. Accordingly, the carryout part is not needed and not provided with patentable weight given the “or” statement.
With regard to claims 6 and 15, Shukla further discloses: identifying, by the vehicle system, at least one user among the at least one passenger detected based on one or more user records stored in a datastore characteristics of the at least one passenger including at least one of a portable computing device associated with the passenger, facial features identified from image data (see page 8, “In some examples, the assistant may identify that there are five people walking within a proximity of the user, and in the same direction as the user, indicating that they are associated with the user. The image analysis may also identify whether there are any children in the automobile by identifying a child car seat or child toys. This may be beneficial, for example, because the assistant may notify a host or hostess, or provide a note if making an online reservation, that a child seat will be needed.” Where the outside face of the toys/child seat indicate, based on the knowledge/memory/database of the system, that a child is present and accommodations may be necessary), or a combination thereof; and recommending, by the vehicle system, a food item for the carryout order based on a user record associated with the at least one user identified (carry out order not applied.).
With regard to claims 8 and 17, Shukla discloses claim 1. Shukla was applied to the schedule reservation part of the “or” statement, not the carryout part. Accordingly, the carryout part is not needed and not provided with patentable weight given the “or” statement.
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.
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.
Claims 7, 16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Shukla in view of U.S. Pat. Pub. No. 2006/0161342 to Tomoda (“Tomoda”).
With regard to claims 7, 16, and 20, Shukla does not teach claim 7. However, Tomoda at e.g. Fig. 4, published claim 8, [0014] [0056] [0059-60] [0066-67] teaches that it would have been obvious to one of ordinary skill in the vehicular device/navigation system art to include the ability to provide, by the vehicle system, a recommendation of one or more restaurants provided within a selected distance from the vehicle upon detecting that the vehicle has traveled a predefined time or a predefined distance without stopping, where the system recommends the rest stop after a predetermined time of driving, and further the recommendation is on the recommended route. Therefore, it would have been obvious to one of ordinary skill in the vehicular device art before the effective filing date of the claimed invention to modify Shukla to include such recommendation feature in order to remind the driver that they need to take a break as humans have a tendency to get tired while driver for longer periods of time, and the advantage is that with a break the driver is able to wake up and move around at the rest stop. [0066] of Tomoda indicates that when the driver says no, I don’t need a rest stop, the system can get increasingly shorter in time period between the next notification, such that the system starts reminding in a quicker fashion the longer the driver drives without stopping. Again, this is a safety feature recommendation so that the driver does not fall asleep at the wheel, or make a mistake driving due to needing a break.
Claims 9 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Shukla in view of U.S. Pat. Pub. No. 2014/0066110 to Lovegreen (“Lovegreen”).
With regard to claims 9 and 18, Shukla does not disclose claims 9 and 18. However, Lovegreen teaches at e.g. Fig. 2 central server sends message to guest associated with the car, central server verifies from guest with vehicle, central server sends message to valet supervisor to tell employee to retrieve specific vehicle for specific detected guest, central server then notifies guest that vehicle is ready. Therefore, it would have been obvious to one of ordinary skill in the vehicular art before the effective filing date of the claimed invention to modify Shukla to include such valet features, as this deals with some of the issues with paper tickets (Lovegreen [0008-10]) including that this solves the problem that the guest used to have to wait for the valet to get the car when they show up to retrieve the car, and with this they can indicate that they want the car now, and when the car shows up, they will be notified on their phone or some other device so they can wait where they want, not at the valet stand. This creates a better customer experience and increases loyalty. See also Lovegreen [0011-12].
Response to Arguments
The examiner has reviewed Applicant’s arguments in totality.
For the 101 rejection, the examiner has withdrawn the 101 rejections based on the amendments/arguments provided. In particular, the examiner finds that the claims integrate the abstract idea into practical application, thereby providing a technological improvement, by e.g. detecting by vehicle system number of passengers, identifying one passenger, determining that the passenger is dinein or dineout, establish communication link between vehicle system and restaurant terminal, and schedule reservation via the established communication link. This is a technological improvement to the vehicle system/restaurant terminal art. Accordingly, the 101 rejection is withdrawn.
For the 103 rejection, the examiner refers to the specifics of the rejection, where the specific claims amendments/arguments are addressed.
Conclusion
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/PETER LUDWIG/Primary Examiner, Art Unit 3627
1 For Shukla, in making a reservation based on amount of people and time, this is inherently dine in. For a pickup food order, the food order would have to be placed and there is no indication that a food order is placed from the vehicle, in Shukla.
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