DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. 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
2. Applicant's arguments filed 07/23/2025 have been fully considered but they are not persuasive.
3. Applicant argues the amended claim(s) 1 is/are allowable over Aich et al. (US-20200104962-A1) and the other cited references. Applicant continues, the cited references fail to disclose newly amended feature of “in response to a triggering condition comprising at least one of a new passenger joining the shared ride or one of the passengers leaving the shared ride, dynamically determining an updated consensus preference for the condition based on the current individual preferences of the passengers, and applying the updated consensus preference for at least a portion of the shared ride.”
4. Indeed, these references do not teach the newly amended feature(s) above. As such, this amendment has necessitated additional reference Boston et al. (US-20200307352-A1) which teaches, in brief, a system 200 for optimizing climate control includes an autonomous vehicle 204 that provides transportation services, such as ride-sharing and/or taxi services, for users ([0021], Fig. 2). Preferences associated with a user may be maintained by the computing device 202 and accessed by the cloud server 208 upon receiving a request for an autonomous vehicle 204 from the user ([0025]). The set temperature may be determined by an algorithm based on previous desired temperatures of users requesting rides under similar circumstances ([0029]). The set temperature 410 may be maintained substantially constant throughout the duration of the ride, from the time the autonomous vehicle 204 reaches the pickup location until the time the user exits 412 the autonomous vehicle 204. Adjustments to the set temperature 410 may be made throughout the duration of the ride. Multiple adjustments may be needed to accommodate the preferences of additional riders picked up by the same autonomous vehicle 204 ([0036]). Picking up additional riders or a rider exiting the vehicle are the triggering condition of a new passenger joining the shared ride or one of the passengers leaving the shared ride. Adjusting the temperature when an additional rider is picked up or exits the vehicle encompasses dynamically determining an updated consensus preference for the condition based on the current individual preferences of the passengers and applying the updated consensus preference for at least a portion of the shared ride.
5. As such, Aich, in view of Boston, teaches each and every limitation of these claims and this argument is moot.
6. Applicant argues independent claim(s) 12 and 18 has/have been amended similar to independent claim 1 and it/they is/are allowable for reasons similar to those presented in favor of patentability of claim 1.
7. This argument is unpersuasive as each independent claim has been fully rejected and for the reasons given above.
8. Applicant argues dependent claim(s) is/are patentable by the virtue of their dependency on one of the independent claims.
9. This argument is unpersuasive as each independent claim and dependent claim has been fully rejected and for the reasons given above.
Claim Rejections - 35 USC § 103
10. 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.
11. Claim(s) 1-7, 9, 11-16, and 18-20
is/are rejected under 35 U.S.C. 103 as being unpatentable over Aich et al. (US-20200104962-A1) in view of Boston et al. (US-20200307352-A1).
In regards to claim 1
, Aich teaches A method of managing a condition of a shared ride provided using an autonomous vehicle (AV), the method comprising: (Figs. 8-11, [0002] Systems and methods that allow a customer to personalize a ride in a vehicle of a transportation service. [0019] The customer is a rider in a vehicle shared by other passengers such as in a ride sharing environment. [0040] Various types of vehicles are used with different numbers or configurations of capacity, including autonomous vehicles without dedicated drivers.)
determining individual preferences for the condition expressed by passengers participating in the shared ride; ([0085] A system prompts the customer regarding the trip characteristic 904 which is determining individual preferences.)
determining a consensus preference for the condition based on the individual preferences; ([0085] The system prompts multiple customers in order to determine a consensus among riders in a vehicle.)
applying the consensus preference for the condition for at least a portion of the shared ride, wherein the applying the consensus preference for the condition comprises managing settings of the AV, including settings of a cabin of the AV; and ([0090] A system sends a message to the vehicle or the driver of the vehicle to modify the trip characteristic 910 which encompasses applying the consensus preference for the condition for at least a portion of the shared ride. The system can automatically play music, run a movie, set a temperature, open windows, etc. which is managing settings of the AV, including settings of a cabin of the AV.)
Further, Aich teaches for automatically adjusting a trip characteristic, a system such as a transit service determines that a customer is waiting for a vehicle or is in the vehicle 1102 (Fig. 11, step 1102, [0100]) which is a new passenger joining the shared ride.
Aich does not explicitly teach in response to a triggering condition comprising at least one of a new passenger joining the shared ride or one of the passengers leaving the shared ride:
dynamically determining an updated consensus preference for the condition based on the current individual preferences of the passengers; and
applying the updated consensus preference for at least a portion of the shared ride.
However, Boston teaches a system 200 for optimizing climate control includes an autonomous vehicle 204 that provides transportation services, such as ride-sharing and/or taxi services, for users. Users may summon an autonomous vehicle 204 by way of an application on a computing device 202, such as a cell phone, tablet, laptop computer, desktop computer, or the like ([0021], Fig. 2). A user may have certain preferences as to the inside temperature and/or climate of the autonomous vehicle 204. Preferences associated with a user may be maintained by the computing device 202 and accessed by the cloud server 208 upon receiving a request for an autonomous vehicle 204 from the user ([0025]). The set temperature may be determined by an algorithm based on previous desired temperatures of users requesting rides under similar circumstances ([0029]). The set temperature 410 may be maintained substantially constant throughout the duration of the ride, from the time the autonomous vehicle 204 reaches the pickup location until the time the user exits 412 the autonomous vehicle 204. Adjustments to the set temperature 410 may be made throughout the duration of the ride. Multiple adjustments may be needed to accommodate the preferences of additional riders picked up by the same autonomous vehicle 204 ([0036]). Picking up additional riders or a rider exiting the vehicle are the triggering condition of a new passenger joining the shared ride or one of the passengers leaving the shared ride. Adjusting the temperature when an additional rider is picked up or exits the vehicle encompasses dynamically determining an updated consensus preference for the condition based on the current individual preferences of the passengers and applying the updated consensus preference for at least a portion of the shared ride.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify transportation management service of Aich, by incorporating the teachings of Boston, such that when an additional rider is picked up, a condition of the autonomous vehicle, such as the inside temperature of the autonomous vehicle, is set to accommodate the preferences of additional rider along with the existing riders.
The motivation to modify is that, as acknowledged by Boston, to ensure an autonomous vehicle cabin is maintained at a comfortable temperature for passengers while minimizing the amount of energy consumed during times when the vehicle is unoccupied ([0006]) which one of ordinary skill would have recognized allows the operation of the vehicle to be cost efficient and would automatically tailor temperature and climate control settings to particular users.
In regards to claim 2
, Aich, as modified by Boston, teaches The method of claim 1, wherein the determining the consensus preference for the condition based on the individual preferences comprises calculating an average of the individual preferences, wherein the average of the individual preferences comprises the consensus preference. ([0061]-[0062] Users can either suggest route information or provide information that corresponds to a route that would be desired by the user. This can include, an origination location, a destination location, a desired pickup time, and a desired drop-off time which acts as the individual preferences. A route optimization module 720 performs an optimization process using the provided routing options to determine an appropriate set of routes to provide in response to the various requests. Such an optimization is performed for each received request, in a dynamic vehicle routing system, or for a batch of requests, where users submit requests and then receive routing options at a later time. The route optimization module 720 applies the objective function to determine the route quality scores and then selects the set of options that provides the highest overall, or highest average, total quality score. Various other approaches are used as well as would be understood to one of ordinary skill in the art in light of the teachings and suggestions contained herein. As mentioned above, the route information is an individual preference and highest average quality score of the route is used by the optimization module which is calculating an average of the individual preferences, wherein the average of the individual preferences comprises the consensus preference.)
In regards to claim 3
, Aich, as modified by Boston, teaches The method of claim 2, wherein the calculating the average further comprises applying weights to the individual preferences prior to calculating the average. ([0065] Artificial intelligence-inclusive approaches, such as those that utilize machine learning, is used with the optimization algorithms to further improve the performance over time. The raising and lowering of various factors results in a change in ridership levels, customer reviews, and the like, as well as actual costs and timing, is fed back into a machine learning algorithm to learn the appropriate weightings, values, ranges, or factors to be used with an optimization function. As mentioned above, appropriate weightings are determined and used with the optimization function. When the optimization function uses highest average, as taught by claim 2, then the optimization functions is calculating the average by applying weights to the individual preferences prior to calculating the average.)
In regards to claim 4
, Aich, as modified by Boston, teaches The method of claim 3, wherein, for each of the individual preferences, the weight applied thereto is based on at least one of a relative status of the passenger, a queue position of the passenger, a ride length of the passenger, and a health condition of the passenger. ([0050] A rider's convenience score takes into account various factors. Various other factors are taken into account as well, including ride length, number of stops, destination time, anticipated traffic, and other such factors. The convenience value itself is a weighted combination of these and other such factors. As mentioned above, Aich suggests other factors are taken into account which encompasses relative status of the passenger, a queue position of the passenger, and a health condition of the passenger. [0070] If the customer is of a certain status with the transportation system, the customer receives preferential treatment. The seat assignment is based on interpersonal preferences for a customer.)
In regards to claim 5
, Aich, as modified by Boston, teaches The method of claim 1, wherein the individual preferences are specified in user profiles associated with the passengers participating in the shared ride. ([0074] The prompt can regard the customer's preferences or biographical information and can be used to build or update a profile for the customer. [0079] A system updates a customer profile based on the response 814. The customer might have a profile with the transportation service and/or the system that received the response. Such a profile might be created by the customer or can be a backend profile that monitors the customer's preferences without the customer needing to create a profile.)
In regards to claim 6
, Aich, as modified by Boston, teaches The method of claim 1, wherein the individual preferences are indicated by the passengers on a per-ride basis via user ridesharing application displayed on mobile devices of the passengers. (Fig. 2, [0025]-[0027] An electronic device display 200 is connected to a communications network for a service that coordinates and/or provides rides for customers. The electronic device display 200 can be owned by the customer or associated with a seat of the customer. The electronic device display 200 presents a trip preferences prompt 204 for inquiring the preferences of the customer. The customer specifies that the customer prefers certain atmospheric attributes. As mentioned above, the customer preferences are set through an electronic device that is owned by the customer which is the mobile devices of the passengers.)
In regards to claim 7
, Aich, as modified by Boston, teaches The method of claim 1, wherein the determining the consensus preference for the condition based on the individual preferences comprises selecting one of the individual preferences, wherein the selected one of the individual preference comprises an individual preference expressed by a majority of the passengers. ([0088] A system determines that a predefined number of responses agree 908. For certain trip characteristics, the change is ratified based on a certain number of votes. For some trip characteristics, if one customer responds a certain way, then the one response will be determinative of the outcome of the characteristic. For other trip characteristics, a plurality, majority, or unanimity is required to determine the trip characteristic.)
In regards to claim 9
, Aich, as modified by Boston, teaches The method of claim 1,
wherein applying the updated consensus preference for the at least a portion of the shared ride comprises managing the settings of the AV, including settings of a cabin of the AV.
Further, Boston teaches adjustments to the set temperature 410 may be made throughout the duration of the ride. Multiple adjustments may be needed to accommodate the preferences of additional riders picked up by the same autonomous vehicle 204 ([0036]). The Examiner assets the temperature is a setting of a cabin of the AV and adjustments to the set temperature is managing the settings of the AV.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify transportation management service of Aich, as already modified by Boston, by further incorporating the teachings of Boston, such that the inside temperature of the autonomous vehicle is set to accommodate the preferences of additional rider along with the existing riders.
The motivation to do so is the same as acknowledged by Boston in regard to claim 1.
In regards to claim 11
, Aich, as modified by Boston, teaches The method of claim 1, wherein the condition comprises one of heating ventilation and cooling (HVAC) settings for the cabin, a brightness level of lighting within the cabin, a volume of audio within the cabin, a music genre, and a level of social interaction. ([0029] The trip preferences prompt 204 pertains to characteristics of the particular ride, such as whether the customer wants the windows down or up at that moment. Other characteristics for the current ride include a type of media playing (e.g., a movie or music), a selection of media, a volume or brightness of media, an overhead light setting, a windows down/up preference, a preferred temperature, a preferred humidity, an artificial fragrance preference, a fan speed for internal air, etc.)
In regards to claim 12
, Aich teaches A method of managing a condition of a shared ride provided using an autonomous vehicle (AV), the method comprising: (Figs. 8-11, [0002] Systems and methods that allow a customer to personalize a ride in a vehicle of a transportation service. [0019] The customer is a rider in a vehicle shared by other passengers such as in a ride sharing environment. [0040] Various types of vehicles are used with different numbers or configurations of capacity, including autonomous vehicles without dedicated drivers.)
determining an individual preference for the condition expressed by a primary passenger participating in the shared ride; (Figs. 8-11, [0070] If the customer is of a certain status with the transportation system, the customer receives preferential treatment. A customer of a certain status with the transportation system acts as the primary passenger. [0085] A system prompts the customer regarding the trip characteristic 904 which is determining individual preferences which encompasses determining an individual preference for a condition of a shared ride expressed by a primary passenger.)
determining individual preferences for the condition expressed by candidate shared ride passengers; ([0085] A system prompts the customer regarding the trip characteristic 904 which is determining individual preferences and encompasses determining individual preferences for the condition expressed by candidate shared ride passengers.)
comparing the individual preference expressed by the primary passenger with the individual preferences expressed by the candidate passengers; ([0088] For some trip characteristics, a plurality, majority, or unanimity is required to determine the trip characteristic. Determining a plurality, majority, or unanimity requires comparing the individual preferences.)
selecting based at least in part on the comparing at least one of the candidate passengers to participate in the shared ride with the primary passenger; and ([0088] For some trip characteristics, a plurality, majority, or unanimity is required to determine the trip characteristic. Determining a plurality based on the preferences of two passengers, especially when one of the passengers is the customer that receives preferential treatment, encompasses selecting based at least in part on the comparing at least one of the candidate passengers to participate in the shared ride with the primary passenger.)
Further, Aich teaches for automatically adjusting a trip characteristic, a system such as a transit service determines that a customer is waiting for a vehicle or is in the vehicle 1102 (Fig. 11, step 1102, [0100]) which is a new passenger joining the shared ride.
Aich does not explicitly teach in response to a triggering condition comprising at least one of a new passenger joining the shared ride or one of the passengers leaving the shared ride:
dynamically determining an updated consensus preference for the condition based on the current individual preferences of the passengers; and
applying the updated consensus preference for at least a portion of the shared ride.
However, Boston teaches a system 200 for optimizing climate control includes an autonomous vehicle 204 that provides transportation services, such as ride-sharing and/or taxi services, for users. Users may summon an autonomous vehicle 204 by way of an application on a computing device 202, such as a cell phone, tablet, laptop computer, desktop computer, or the like ([0021], Fig. 2). A user may have certain preferences as to the inside temperature and/or climate of the autonomous vehicle 204. Preferences associated with a user may be maintained by the computing device 202 and accessed by the cloud server 208 upon receiving a request for an autonomous vehicle 204 from the user ([0025]). The set temperature may be determined by an algorithm based on previous desired temperatures of users requesting rides under similar circumstances ([0029]). The set temperature 410 may be maintained substantially constant throughout the duration of the ride, from the time the autonomous vehicle 204 reaches the pickup location until the time the user exits 412 the autonomous vehicle 204. Adjustments to the set temperature 410 may be made throughout the duration of the ride. Multiple adjustments may be needed to accommodate the preferences of additional riders picked up by the same autonomous vehicle 204 ([0036]). Picking up additional riders or a rider exiting the vehicle are the triggering condition of a new passenger joining the shared ride or one of the passengers leaving the shared ride. Adjusting the temperature when an additional rider is picked up or exits the vehicle encompasses dynamically determining an updated consensus preference for the condition based on the current individual preferences of the passengers and applying the updated consensus preference for at least a portion of the shared ride.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify transportation management service of Aich, by incorporating the teachings of Boston, such that when an additional rider is picked up, a condition of the autonomous vehicle, such as the inside temperature of the autonomous vehicle, is set to accommodate the preferences of additional rider along with the existing riders.
The motivation to do so is the same as acknowledged by Boston in regard to claim 1.
In regards to claim 13
, Aich, as modified by Boston, teaches The method of claim 12, wherein the individual preferences are specified in user profiles associated with the passengers. ([0074] The prompt can regard the customer's preferences or biographical information and can be used to build or update a profile for the customer. [0079] A system updates a customer profile based on the response 814. The customer might have a profile with the transportation service and/or the system that received the response. Such a profile might be created by the customer or can be a backend profile that monitors the customer's preferences without the customer needing to create a profile.)
In regards to claim 14
, Aich, as modified by Boston, teaches The method of claim 12, wherein the individual preferences are indicated by the passengers on a per-ride basis via user ridesharing application displayed on mobile devices of the passengers. (Fig. 2, [0025]-[0027] An electronic device display 200 is connected to a communications network for a service that coordinates and/or provides rides for customers. The electronic device display 200 can be owned by the customer or associated with a seat of the customer. The electronic device display 200 presents a trip preferences prompt 204 for inquiring the preferences of the customer. The customer specifies that the customer prefers certain atmospheric attributes. As mentioned above, the customer preferences are set through an electronic device that is owned by the customer which is the mobile devices of the passengers.)
In regards to claim 15
, Aich, as modified by Boston, teaches The method of claim 12, wherein the selecting comprises selecting the at least one of the candidate passengers whose individual preference for the condition is identical to the individual preference of the primary passenger. ([0088] For some trip characteristics, a plurality, majority, or unanimity is required to determine the trip characteristic. [0097] If the preference is that the customer wishes for a social environment while travelling, then an itinerary is chosen based on whether the itinerary includes other similarly socially inclined individuals which is selecting the at least one of the candidate passengers whose individual preference for the condition is identical to the individual preference of the primary passenger, especially when the primary passenger is a socially inclined individual.)
In regards to claim 16
, Aich, as modified by Boston, teaches The method of claim 12, wherein the selecting comprises selecting the at least one of the candidate passengers whose individual preference for the condition is acceptable to the primary passenger. ([0088] For some trip characteristics, a plurality, majority, or unanimity is required to determine the trip characteristic. [0097] If the preference is that the customer wishes for a social environment while travelling, then an itinerary can be chosen based on whether the itinerary includes other similarly socially inclined individuals which is selecting the at least one of the candidate passengers whose individual preference for the condition is acceptable to the primary passenger, especially when the primary passenger is a socially inclined individual.)
In regards to claim 18
, Aich teaches One or more non-transitory computer-readable storage media comprising instruction for execution which, when executed by a processor, are operable to perform operations for providing remote assistance to a vehicle, the operations comprising: ([0111] Various types of non-transitory computer-readable storage media is used for storing instructions or code that is executed by at least one processor for causing the system to perform various operations.)
determining an individual preference for a condition of a shared ride expressed by a primary passenger participating in the shared ride (Figs. 8-11, [0070] If the customer is of a certain status with the transportation system, the customer receives preferential treatment. A customer of a certain status with the transportation system acts as the primary passenger. [0085] A system prompts the customer regarding the trip characteristic 904 which is determining individual preferences which encompasses determining an individual preference for a condition of a shared ride expressed by a primary passenger.), wherein the shared ride is provided using an autonomous vehicle (AV); ([0019] The customer is a rider in a vehicle shared by other passengers such as in a ride sharing environment. [0040] Various types of vehicles are used with different numbers or configurations of capacity, including autonomous vehicles without dedicated drivers.)
determining individual preferences for the condition expressed by candidate shared ride passengers; ([0085] A system prompts the customer regarding the trip characteristic 904 which is determining individual preferences which encompasses determining individual preferences for the condition expressed by candidate shared ride passengers.)
comparing the individual preference expressed by the primary passenger with the individual preferences expressed by the candidate passengers; ([0088] For some trip characteristics, a plurality, majority, or unanimity is required to determine the trip characteristic. Determining a plurality, majority, or unanimity requires comparing the individual preferences.)
selecting based at least in part on the comparing at least one of the candidate passengers to participate in the shared ride with the primary passenger; ([0088] For some trip characteristics, a plurality, majority, or unanimity is required to determine the trip characteristic. Determining a plurality based on the preferences of two passengers, especially when one of the passengers is the customer that receives preferential treatment, encompasses selecting based at least in part on the comparing at least one of the candidate passengers to participate in the shared ride with the primary passenger.)
determining a consensus preference for the condition based on the individual preference of the primary passenger and the individual preference of the selected at least one of the candidate passengers; ([0085] The system prompts multiple customers in order to determine a consensus among riders in a vehicle. [0070] If the customer is of a certain status with the transportation system, the customer receives preferential treatment. Receiving preferential treatment, such as applying the preferences of the customer of a certain status is determining a consensus preference for the condition based on the individual preference of the primary passenger and the individual preference of the selected at least one of the candidate passengers.)
applying the consensus preference for the condition for at least a portion of the shared ride, wherein the applying the consensus preference for the condition comprises managing settings of the AV, including settings of a cabin of the AV; and ([0090] A system sends a message to the vehicle or the driver of the vehicle to modify the trip characteristic 910 which encompasses applying the consensus preference for the condition for at least a portion of the shared ride. The system can automatically play music, run a movie, set a temperature, open windows, etc. which is managing settings of the AV, including settings of a cabin of the AV.)
Further, Aich teaches for automatically adjusting a trip characteristic, a system such as a transit service determines that a customer is waiting for a vehicle or is in the vehicle 1102 (Fig. 11, step 1102, [0100]) which is a new passenger joining the shared ride.
Aich does not explicitly teach in response to a triggering condition comprising at least one of a new passenger joining the shared ride or one of the passengers leaving the shared ride:
dynamically determining an updated consensus preference for the condition based on the current individual preferences of the passengers; and
applying the updated consensus preference for at least a portion of the shared ride.
However, Boston teaches a system 200 for optimizing climate control includes an autonomous vehicle 204 that provides transportation services, such as ride-sharing and/or taxi services, for users. Users may summon an autonomous vehicle 204 by way of an application on a computing device 202, such as a cell phone, tablet, laptop computer, desktop computer, or the like ([0021], Fig. 2). A user may have certain preferences as to the inside temperature and/or climate of the autonomous vehicle 204. Preferences associated with a user may be maintained by the computing device 202 and accessed by the cloud server 208 upon receiving a request for an autonomous vehicle 204 from the user ([0025]). The set temperature may be determined by an algorithm based on previous desired temperatures of users requesting rides under similar circumstances ([0029]). The set temperature 410 may be maintained substantially constant throughout the duration of the ride, from the time the autonomous vehicle 204 reaches the pickup location until the time the user exits 412 the autonomous vehicle 204. Adjustments to the set temperature 410 may be made throughout the duration of the ride. Multiple adjustments may be needed to accommodate the preferences of additional riders picked up by the same autonomous vehicle 204 ([0036]). Picking up additional riders or a rider exiting the vehicle are the triggering condition of a new passenger joining the shared ride or one of the passengers leaving the shared ride. Adjusting the temperature when an additional rider is picked up or exits the vehicle encompasses dynamically determining an updated consensus preference for the condition based on the current individual preferences of the passengers and applying the updated consensus preference for at least a portion of the shared ride.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify transportation management service of Aich, by incorporating the teachings of Boston, such that when an additional rider is picked up, a condition of the autonomous vehicle, such as the inside temperature of the autonomous vehicle, is set to accommodate the preferences of additional rider along with the existing riders.
The motivation to do so is the same as acknowledged by Boston in regard to claim 1.
In regards to claim 19
, Aich, as modified by Boston, teaches The one or more non-transitory computer-readable storage media of claim 18, wherein the individual preferences of the candidate passengers and the individual preference of the primary passenger are specified in user profiles associated with the passengers. ([0074] The prompt can regard the customer's preferences or biographical information and can be used to build or update a profile for the customer. [0079] A system can update a customer profile based on the response 814. The customer might have a profile with the transportation service and/or the system that received the response. Such a profile might be created by the customer or can be a backend profile that monitors the customer's preferences without the customer needing to create a profile.)
In regards to claim 20
, Aich, as modified by Boston, teaches The one or more non-transitory computer-readable storage media of claim 18, wherein the individual preferences of the candidate passengers and the individual preference of the primary passenger are indicated by the passengers on a per-ride basis via user ridesharing application displayed on mobile devices of the passengers. (Fig. 2, [0025]-[0027] An electronic device display 200 is connected to a communications network for a service that coordinates and/or provides rides for customers. The electronic device display 200 can be owned by the customer or associated with a seat of the customer. The electronic device display 200 presents a trip preferences prompt 204 for inquiring the preferences of the customer. The customer specifies that the customer prefers certain atmospheric attributes. As mentioned above, the customer preferences are set through an electronic device that is owned by the customer which is the mobile devices of the passengers.)
12. Claim(s) 8
is/are rejected under 35 U.S.C. 103 as being unpatentable over Aich et al. (US-20200104962-A1) in view of Boston et al. (US-20200307352-A1) and further in view of Cao (US-20160364823-A1).
In regards to claim 8
, Aich, as modified by Boston, teaches The method of claim 1.
Aich, as modified by Boston, does not teach wherein the determining the consensus preference for the condition comprises:
presenting a challenge to the passengers;
determining a winner of the challenge, wherein the winner comprises one of the passengers; and
assigning the individual preference of the winner of the challenge as the consensus preference.
However, Cao teaches a system that provides transparent bidding for vehicles, car rental/borrowing, rideshare matching, and/or package delivery ([0067]). In Transparent bidding, each member knows the others' bids as transparency is an important feature of the system. The system shows only the current winning bid and number of bids so far and ending time. Moreover, it also should allow members for bid at the last seconds. Biddings can be Closed bidding vs. Open bidding. In Closed Bidding, the members should send a bid message to the organizer who will announce the winning bid number, but that takes away the competition for money in the Open Bidding process that will benefit all members. Open Bidding will drive the winning bid down and the winner will be the person who needs the ride the most in the bidding cycle, and that person is willing to pay the highest ([0097]-[0098]). A ride auction component may administer bidding between one or more passengers 104 for a seat in a vehicle 110 along a particular route 108. The carpool matching transaction system may also take into account rideshare participation incentives administered by a rideshare participation incentives component ([0103]). Transparent bidding is presenting a challenge to the passengers and a seat is user preference.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify transportation management service of Aich, as already modified by Boston, by incorporating the teachings of Cao, such that a challenge, such as bidding, is presented to the passengers and the passengers can bid and upon determining the winner, the preferences of the winner is applied.
The motivation to modify is that, as acknowledged by Cao, the car sharing/riding system improves utilization of a car, which sits idle an average of 22 hours per day while costing owners loan/lease payments, maintenance, parking and insurance The system turns an underutilized, expensive possession into an asset that has a real economic and environmental impact in the community Each shared vehicle removes approximately 15 personally owned vehicles from the road ([0020]) which one of ordinary skill would have recognized allows CO2 emissions as the result of manufacturing a new car to decrease.
13. Claim(s) 17
is/are rejected under 35 U.S.C. 103 as being unpatentable over Aich et al. (US-20200104962-A1) in view of Boston et al. (US-20200307352-A1) and further in view of Arditi (US-20190197430-A1).
In regards to claim 17
, Aich, as modified by Boston, teaches The method of claim 12, further comprising rejecting a candidate passenger for inclusion in the shared ride based on a conflict between the individual preference of the candidate passenger and the individual preference of the primary passenger, ([0061] Customers may also request for specific locations and times where deviation is not permissible, and the route manager needs to either determine an acceptable routing option or deny that request if minimum criteria are not met which encompasses rejecting a candidate passenger for inclusion in the shared ride based on a conflict between the individual preference of the candidate passenger and the individual preference of the primary passenger.)
Aich, as modified by Boston, does not teach wherein the individual preferences relate to a health condition.
However, Arditi teaches systems, apparatuses, and methods for providing personalized ride experiences to users of a transportation management system. A transportation management system facilitates ride sharing between ride providers and ride requestors and/or manage a fleet of autonomous vehicles to fulfill transportation needs of ride requestors. To improve the ride experience for ride requestors, the transportation management system leverages the system's knowledge of ride requestors to determine ride preferences, which is personalized for individual ride requestors, and instruct devices associated with the ride provider to actuate those ride preferences, such as playing the preferred type of music and/or adjusting the temperature to a preferred level. Sensors in the vehicle are used to capture real-time sensor data associated with the ride requestor. The real-time sensor data is processed using one or more machine-learning models trained based on similar types of data to predict real-time features of the ride requestor. The real-time features includes, the ride requestor's current mood, stress level, comfort level with respect to vehicle amenities (e.g., temperature, audio, entertainment, etc.), health condition, and/or any other features that is characterize or represent the requestor's current state. Interior sensor data is used to detect and respond to emergencies, such as urgent health conditions, appropriately ([0021]-[0022]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the application to modify transportation management service of Aich, as already modified by Boston, by incorporating the teachings of Arditi, such that a customer’s ride request is rejected when the primary passenger preference indicates an health condition or a health related emergency.
The motivation to modify is that, as acknowledged by Arditi, to coordinate personal preferences amongst riders in a ridesharing system ([0003]) which one of ordinary skill would have recognized allows passenger to enjoy a pleasant ride with other passengers.
Conclusion
14. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Liu (US-11724714-B2) teaches autonomous vehicles utilized by ridesharing and/or delivery services.
Sanchez (US-20230146426-A1) teaches conditional bids for a target operator profile.
15. 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).
16. 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.
17. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Preston J Miller whose telephone number is (703)756-1582. The examiner can normally be reached Monday through Friday 7:30 AM - 4:30 PM EST.
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/P.J.M./Examiner, Art Unit 3661
/RAMYA P BURGESS/Supervisory Patent Examiner, Art Unit 3661