DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Final Office Action is in reply to the amendments/remarks filed on 27 May 2025.
Claims 1-20 are currently pending and have been examined.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more, and therefore directed to non-statutory subject matter.
Under Step 1, the claims 1-20 recite a method (i.e. a process). Thus the claims fall within one of the four statutory categories. See MPEP 2106.03.
Under Step 2A Prong 1, the claims are analyzed to determine whether the claims recite any judicial exceptions including certain groupings of abstract ideas (i.e., mathematical concepts, certain methods of organizing human activity such as a fundamental economic practice, or mental processes).
Claim 1 recites in part, aggregating data collected…; matching the data against one or more templates, wherein the templates define as a criterion of user achievement, an operation performed by an autonomous vehicle that serviced the user…; generating a digital token corresponding to a matched template…
Under their broadest reasonable interpretation, the limitations can be considered as belonging to methods of organizing human activity abstract idea category since they are directed to steps for determining a user’s achievement and generating a digital token based on the user’s achievement. This is a method of managing personal behavior. Thus, the claim recites an abstract idea. See MPEP 2106.02 (a)(2) subsection II, C.
Additionally the claims can be considered as a mental process abstract idea category as they are related to aggregating data collected…; matching the data against one or more templates, wherein the templates define as a criterion of user achievement, an operation performed by an autonomous vehicle that serviced the user…; generating a digital token corresponding to a matched template; generating a digital token corresponding to a matched template. The steps of aggregating, matching, generating mimic human thought processes of observation, evaluation, judgment, and opinion, perhaps with paper and pencil. Accordingly, the claim recites an abstract idea. See 2106.04(a)(2) subsection III.
Claim 10 recites, aggregating data collected…; checking the data against one or more thresholds, wherein the thresholds are numerical values indicating as a criterion of user achievement, an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme; in response to the data crossing a threshold, generating a digital token corresponding to the crossed threshold...
Under their broadest reasonable interpretation, the limitations can be considered as belonging to methods of organizing human activity abstract idea category since they are directed to steps for determining a user’s achievement and generating a digital token to the user based on the user’s achievement. This is a method of managing personal behavior. Thus the claim recites an abstract idea. See MPEP 2106.02 (a)(2) subsection II, C.
Additionally the claims can be considered as a mental process abstract idea category as they are directed to aggregating data collected…; checking the data against one or more thresholds, wherein the thresholds are numerical values indicating as a criterion of user achievement, an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme; in response to the data crossing a threshold, generating a digital token corresponding to the crossed threshold. The steps of aggregating, checking, and generating mimic human thought processes of observation, evaluation, judgment, and opinion, perhaps with paper and pencil. Accordingly, the claim recites an abstract idea. See 2106.04(a)(2) subsection III.
Under their broadest reasonable interpretation, the limitations of claim 15 can be considered as belonging to the mental process abstract idea category as they are directed to aggregating data…; finding different patterns based on the aggregated data, the patterns indicating an operation performed by the one or more autonomous vehicles,…; associating the different patterns to different digital tokens; matching data specific to the user to the different patterns. The steps of aggregating, finding, associating and matching mimic human thought processes of observation, evaluation, judgment, and opinion, perhaps with paper and pencil. Accordingly, the claim recites an abstract idea. See MPEP 2106.04(a)(2), subsection III.
Dependent claims 2-5, 8 further reiterate the abstract idea as identified in claim 1 with further embellishments on the types of data collected by the sensors and the type of digital token. The additional limitations of the claims 2-5, and 8 are directed to an abstract idea.
Dependent claims 6-7 recite limitations that can be considered as a mental process abstract idea category as they are related to matching the data against one or more templates…The recited steps do not involve any activities that cannot be practically accomplished by the human mind by evaluating obtained data and comparing the data against a template by human judgement and/or via pen & paper. Accordingly, the claims recite an abstract idea.
Dependent claims 10-13 further reiterate the abstract idea as identified in claim 10 with further embellishments about the thresholds and the digital token. The additional limitations of the claims 10-13 are directed to an abstract idea.
Dependent claim 14 recite limitations that can be considered as a mental process abstract idea category as they are directed to analyzing the data to set a baseline; and the one or more thresholds are set based on the baseline and offset(s) from the baseline. The recited steps do not involve any activities that cannot be practically accomplished by the human mind by evaluating obtained data against a baseline by human judgement and/or via pen & paper. Accordingly, the claim recites an abstract idea.
Dependent claim 16 recites the abstract idea, wherein finding the different patterns comprises: performing clustering on the aggregated data to identify a plurality of classes of users; determining defining characteristics associated with each class of users; and linking the defining characteristics of the classes of users to the different patterns. The limitations can be considered as a mental process abstract idea category because the steps encompass activities that can be practically accomplished by the human mind by evaluating obtained data to identify a plurality of classes of users, evaluating the classes to identify characteristics and associating the characteristics of the classes of users to different patterns by human judgement and/or via pen & paper. Accordingly, the claim recites an abstract idea.
Dependent Claim 17 recites the abstract idea, wherein finding different patterns comprises training a model using labeled data that associates data collected by the one or more sensors to different classes of users; and matching the data specific to the user comprises providing the data specific to the user as input to the trained model and observing an output of the trained model. Under its broadest reasonable interpretation when read in light of the specification, the, “training” and “matching” steps encompass mental processes practically performed in the human mind by observation, evaluation, judgment, and opinion.
Dependent claims 18-20 further reiterate the abstract idea as identified in claim 15 with further embellishments about the patterns. The additional limitations of the claims 18-20 are directed to an abstract idea.
Under Step 2A Prong 2 the claims are analyzed to determine whether the claims recite additional elements that integrate the judicial exception into a practical application.
With respect to claims 1-20, the judicial exception is not integrated into a practical application. In particular, the claims recite additional elements including “sensors”, “digital token” and “user device.” The sensors as recited in the claim limitations are merely a source of data. The digital token as recited in the claims is merely electronic data provided to a user and the user device as recited in the claims is merely used to display data. The additional elements as recited amount no more than mere instructions to apply the exception using generic computer components. The additional elements, causing the digital token to be output to the user on a user device are mere data output recited at a high level of generality, and thus are insignificant extra-solution activity. The limitation, “dispatching another autonomous vehicle to the user” is recited at a high level or generality therefore amount to insignificant post-solution activity. As such, the limitations do not impose any meaningful limits on the claim. See MPEP 2106.05
The combination of these additional elements is also no more than mere instructions to apply the exception using generic computer components and thus fails to add an inventive concept to the claims. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. The claims are directed to an abstract idea.
With respect to claim 9, the additional elements, wherein generating the digital token comprises retrieving a graphic file and/or audio file representing the user achievement are mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity. As such, the limitations do not impose any meaningful limits on the claim. See MPEP 2106.05.
Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
Under Step 2B the claims are analyzed to determine whether the claims recite additional elements that amount to an inventive concept (aka “significantly more”) than the recited judicial exception.
The claims as a whole do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A Prong Two, the additional elements in the claims amount to no more than mere instructions to apply the exception using generic computer components. The same analysis applies here in 2B and does not provide an inventive concept.
For the causing a digital token to be output to the user on a user device step (Claims, 1, 10 and 15) and retrieving step (claim 9) that was considered extra-solution activity in Step 2A, Prong Two, this has been re-evaluated in Step 2B and determined to be well understood, routine, and conventional in the field. The Symantec, TLI, and OIP Techs. court decisions indicate that mere collection or transmission of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). With respect to the limitation, “dispatching another autonomous vehicle to the user” (claims, 1, 10 and 15) that was considered post-solution activity in Step 2A Prong 2, this has been re-evaluated in Step 2B and determined to be well understood, routine, and conventional in the field. As indicated in Uehara et al (US 2020/0265720, paragraph [0003]) dispatching an autonomous vehicle to an occupant is a known (Berkheimer (c), MPEP 2106(5)(D), subsection I). For these reasons, there is no inventive concept. See MPEP 2106.05(d), subsection II.
Considered as an ordered combination, the additional elements of the claim do not add anything further than when they are considered separately. Thus, under Step 2B, the claims are ineligible as the claims do not recite additional elements which result in significantly more than the abstract idea itself.
Claim Rejections - 35 USC § 103
NOTICE: 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 1-7, 10 are rejected under 35 U.S.C. 103 as being unpatentable over Wray et al (US 2022/0274623 A1) in view of Copeland et al (US Patent # 10,942,520 B1) in view of Uehara et al (US 2020/0265720 A1).
Claim 1: Wray discloses a method for generating feedback to a user of autonomous vehicles, the method comprising:
aggregating data collected by one or more sensors mounted on or in one or more autonomous vehicles that serviced the user (see [0062]: In some examples, the gamification controller 3060 may obtain the sensor data via the vehicle controller 3040).
matching the data against one or more templates, wherein the templates define as a criterion of user achievement (see [0067]: In some examples, the method 4000 includes correlating the sensor data with the learning goal. The method 4000 includes determining 4060 the task progress based on the obtained sensor data. If the sensor data indicates that the task is complete, the method 4000 includes transmitting 4070 a notification);
generating a digital token corresponding to a matched template; and in response to generating the digital token: causing a digital token to be output to the user on a user device (see [0062]: a user may earn rewards based on achievements to unlock unique upgrades that may not otherwise be available for purchase in a store. For example, “Drive 10,000 miles on country roads” may be a large-scale goal. In this example, the system may grant the user a badge, such as “The Explorer” that may be added to the customization interface. The reward may unlock a special theme that may not otherwise be purchased. The user interface 3020 may be used to display one or more features to unlock. The one or more features displayed may be based on a number of points stored in the user account 3070. A user may input an unlock request using the user interface 3020).
Wray discloses the user being a driver of an autonomous vehicle. The sole difference between Wray and the claimed subject matter is that Wray does not disclose the user being a user of a ride hail and/or delivery services but Copeland which also discloses a method of awarding a user of an autonomous vehicle with a reward for completing tasks, discloses a method of generating feedback to a user of ride hail and/or delivery services (see col. 6 lines 40-43: route that uses the AV to drive the user from the pickup location to the destination location along the most direct and fastest route from the pickup location to the destination location, taking into consideration current traffic conditions. col. 7 lines 30-50: The example gamification module 208 can provide tasks for the user to perform for rewards points, based on user preferences, when the user is riding in the AV. The user can earn reward points for completing each activity and can earn bonus rewards points for completing all activities).
Since each individual element and its function are shown in the prior art, albeit shown in separate reference, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself- that is in the substitution of the user of ride hail of Copeland for the driver of Wray. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
While Wray and Copeland disclose criteria for a user to earn rewards. Wray, Copeland and Uehara do not explicitly disclose the criteria as being an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme. However, the examiner asserts that the type of criterion as being an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme is simply a label for the data and adds little, if anything, to the claimed acts or steps and thus does not serve to distinguish over the prior art. Any differences related merely to the meaning and information conveyed through labels (i.e., the specific type of criterion) which does not explicitly alter or impact the steps of the method does not patentably distinguish the claimed invention from the prior art in terms of patentability.
Therefore, it would have been obvious to a person of ordinary skill in the art at the time the invention was made to have an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme be included in the reward conditions of Wray combined with Copeland because the type of criteria does not functionally alter or relate to the steps of the method and merely labeling the criteria differently from that in the prior art does not patentably distinguish the claimed invention.
Wray and Copeland do not expressly disclose dispatching another autonomous vehicle to the user but Uehara which also discloses an autonomous vehicle service teaches, dispatching another autonomous vehicle to the user (see [0039]: autonomous driving vehicle falls into an undrivable condition, the dispatch device 2 can dispatch an unfilled vehicle so that an occupant riding in the autonomous driving vehicle can get into another autonomous driving vehicle without delay).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine Wray and Copeland with the method of dispatching another autonomous vehicle to the user as taught by Uehara because it would enable an occupant “get into another autonomous driving vehicle without delay” (Uehara, [0039]).
Claim 2: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 1 above. Wray further teaches, wherein the data collected by the one or more sensors comprises one or more of: starting location, stopping location, and ending location, of one or more trips taken by the one or more autonomous vehicles that serviced the user (see [0060]: An example task to obtain lane information may include an instruction to perform a driving action a predetermined number of times, such as “Drive 2nd Street three times.” [0062]: the gamification controller 3060 may obtain the sensor data via the vehicle controller 3040. The gamification controller 3060 is configured to determine the task progress based on the obtained sensor data).
Claim 3: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 1 above. Wray further teaches, wherein the data collected by the one or more sensors comprises one or more paths traversed in a connected graph; and the one or more paths correspond to one or more trips taken by the one or more autonomous vehicles that serviced the user (connected graph defined in Specification as connected lanes/roads of a map. See [0059]: traversing along the SD map on a small segment to learn a piece of an HD map. An example of a learning goal may be to obtain lane information, such as “Obtain lane lines on 2.sup.nd Street.”).
Claim 4: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 1 above. Wray further teaches, wherein the data collected by the one or more sensors comprises distance traveled for one or more trips taken by the one or more autonomous vehicles that serviced the user ( [0062]: the gamification controller 3060 may obtain the sensor data via the vehicle controller 3040. The gamification controller 3060 is configured to determine the task progress based on the obtained sensor data. For example, “Drive 10,000 miles on country roads” may be a large-scale goal. In this example, the system may grant the user a badge, such as “The Explorer” that may be added to the customization interface).
Claim 5: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 1 above. Wray further teaches, wherein the data collected by the one or more sensors comprises energy consumed for one or more trips taken by the one or more autonomous vehicles that serviced the user (see [0072]: The method 5000 includes determining 5050 whether the task has progressed based on obtained sensor data from one or more sensors, such as sensors 3030 shown in FIG. 3. In some examples, the method 5000 may include transmitting 5060 a progress notification based on the determined progress. In some examples, the method 5000 includes correlating the sensor data with the learning goal. If it is determined that the task has progressed, the method 5000 includes determining 5070 whether the task is complete. If it is determined that the task has not progressed, the method 5000 may include determining 5080 whether a predetermined parameter has been reached. The predetermined parameter may include a duration of time, a number of trip repetitions, a battery consumption threshold).
Claim 6: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 1 above. Copeland further teaches, wherein matching the data against the one or more templates comprises further matching other data that is not collected by the one or more sensors along with the data against the one or more templates (see col. 5 lines 57-60: other information related to trips using the AV can include average user speeds for activities such as walking, running, biking and skating. Other information can be provided by one or more of the third party computer systems 11. Col. 7 lines 40-45: Another example task is for the user to take hybrid trips that include physical activity three times a week. For example, the user can do running on Monday, walking on Wednesday and biking on Friday. Different activities and a different number of days can be used. The user can earn reward points for completing each activity and can earn bonus rewards points for completing all activities).
It would have been would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the correlating the sensor data to reward conditions of Wray, matching other data that is not collected by the one or more sensors along with the data against the one or more templates as taught by Copeland in order to determine rewards points for the user (Copeland, col. 7 lines 40-43).
Claim 7: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 1 above. Wray further teaches, wherein matching the data against the one or more templates comprises determining whether the data meets the criterion of user achievement (see Fig. 5, [0072]: correlating the sensor data with the learning goal. If it is determined that the task has progressed, the method 5000 includes determining 5070 whether the task is complete. If it is determined that the task has not progressed, the method 5000 may include determining 5080 whether a predetermined parameter has been reached. The predetermined parameter may include a duration of time, a number of trip repetitions, a battery consumption threshold, a fuel consumption threshold, or an ambient noise threshold, or any combination thereof).
Claim 10: Wray discloses a method for generating feedback to a user of autonomous vehicles, the method comprising:
aggregating data collected by one or more sensors mounted on or in one or more autonomous vehicles that serviced the user (see [0062]: In some examples, the gamification controller 3060 may obtain the sensor data via the vehicle controller 3040).
checking the data against one or more thresholds, wherein the thresholds are numerical values indicating levels of user achievement (see [0072]: correlating the sensor data with the learning goal. If it is determined that the task has progressed, the method 5000 includes determining 5070 whether the task is complete. If it is determined that the task has not progressed, the method 5000 may include determining 5080 whether a predetermined parameter has been reached. The predetermined parameter may include a duration of time, a number of trip repetitions, a battery consumption threshold, a fuel consumption threshold, or an ambient noise threshold);
in response to the data crossing a threshold, generating a digital token corresponding to the crossed threshold; and in response to generating the digital token: causing a digital token to be output to the user on a user device (see [0062]: user may earn rewards based on achievements to unlock unique upgrades that may not otherwise be available for purchase in a store. For example, “Drive 10,000 miles on country roads” may be a large-scale goal. In this example, the system may grant the user a badge, such as “The Explorer” that may be added to the customization interface).
Wray discloses the user being a driver of an autonomous vehicle. The sole difference between Wray and the claimed subject matter is that Wray does not disclose the user being a user of a ride hail and/or delivery services but Copeland which also discloses a method of awarding a user of an autonomous vehicle with a reward for completing tasks, discloses a method of generating feedback to a user of ride hail and/or delivery services (see col. 6 lines 40-43: route that uses the AV to drive the user from the pickup location to the destination location along the most direct and fastest route from the pickup location to the destination location, taking into consideration current traffic conditions. col. 7 lines 30-50: The example gamification module 208 can provide tasks for the user to perform for rewards points, based on user preferences, when the user is riding in the AV. The user can earn reward points for completing each activity and can earn bonus rewards points for completing all activities).
Since each individual element and its function are shown in the prior art, albeit shown in separate reference, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself- that is in the substitution of the user of ride hail of Copeland for the driver of Wray. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
While Wray and Copeland disclose criteria for a user to earn rewards. Wray, Copeland and Uehara do not explicitly disclose the criteria as being an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme. However, the examiner asserts that the type of criterion as being an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme is simply a label for the data and adds little, if anything, to the claimed acts or steps and thus does not serve to distinguish over the prior art. Any differences related merely to the meaning and information conveyed through labels (i.e., the specific type of criterion) which does not explicitly alter or impact the steps of the method does not patentably distinguish the claimed invention from the prior art in terms of patentability.
Therefore, it would have been obvious to a person of ordinary skill in the art at the time the invention was made to have an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme be included in the reward conditions of Wray combined with Copeland because the type of criteria does not functionally alter or relate to the steps of the method and merely labeling the criteria differently from that in the prior art does not patentably distinguish the claimed invention.
Wray and Copeland do not expressly disclose dispatching another autonomous vehicle to the user but Uehara which also discloses an autonomous vehicle service teaches, dispatching another autonomous vehicle to the user (see [0039]: autonomous driving vehicle falls into an undrivable condition, the dispatch device 2 can dispatch an unfilled vehicle so that an occupant riding in the autonomous driving vehicle can get into another autonomous driving vehicle without delay).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine Wray and Copeland with the method of dispatching another autonomous vehicle to the user as taught by Uehara because it would enable an occupant “get into another autonomous driving vehicle without delay” (Uehara, [0039]).
Claim 14: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 10 above. Wray further teaches: analyzing the data to set a baseline; and the one or more thresholds are set based on the baseline and offset(s) from the baseline (see [0072]: determining 5080 whether a predetermined parameter has been reached. The predetermined parameter may include a duration of time, a number of trip repetitions, a battery consumption threshold, a fuel consumption threshold, or an ambient noise threshold).
Claims 8 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Wray/Copeland/Uehara as applied to claim 1 above, and further in view of Moore ( US 2013/0132959 A1).
Claim 8: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 1 above. Wray, Copeland and Uehara do not expressly disclose the following limitations but Moore which also discloses a method of rewarding a user for completing tasks teaches, generating the digital token comprises generating an animation using the data; and the digital token is personalized to the user (see [0023-0024]: a user may receive or obtain a number of virtual rewards, such as displayable experience points, titles, badges, avatars, avatar animations, avatar accessories, custom virtual buttons).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine in the method of Wray, Copeland and Uehara, generating the digital token comprises generating an animation using the data; and the digital token is personalized to the user as taught by Moore because it would provide higher quality, engaging rewards for users (Moore, [0024]).
Claim 9: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 1 above. Wray, Copeland and Uehara do not expressly disclose the following limitations but Moore which also discloses a method of rewarding a user for completing tasks teaches, wherein generating the digital token comprises retrieving a graphic file and/or audio file representing the user achievement (see [0023]: In addition, rewards may take the form of redeemable coupons, ringtones, songs, for example, that may be distributed electronically (e.g., downloadable, etc.).)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine in the method of Wray, Copeland and Uehara, generating the digital token comprises retrieving a graphic file and/or audio file representing the user achievement as taught by Moore because it would provide higher quality, engaging rewards for users (Moore, [0024]).
Claims 11-13 are rejected under 35 U.S.C. 103 as being unpatentable over Wray/Copeland/Uehara as applied to claim 10 above, and further in view of Scholl et al (US 2020/0074492 A1)
Claim 11: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 10 above. Wray, Copeland and Uehara do not expressly disclose the following limitations but Scholl in the same field of endeavor teaches, wherein: the one or more thresholds includes a plurality of thresholds represented on a scale (see [0044]: if the score is determined to be above a certain threshold. For example, an hour of consecutive undistracted driving may earn the user a silver medal and two hours of consecutive undistracted driving may earn the driver a gold medal).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine in the method of Wray, Copeland and Uehara wherein: the one or more thresholds includes a plurality of thresholds represented on a scale as taught by Scholl because it would “provide customized incentive mechanisms to users to elicit safer driving behavior patterns” (Scholl, [0017]).
Claim 12: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 10 above. Wray, Copeland and Uehara do not expressly disclose the following limitations but Scholl in the same field of endeavor teaches, generating a graphic that indicates meeting or crossing the crossed threshold among other thresholds (see [0044]: if the score is determined to be above a certain threshold. For example, an hour of consecutive undistracted driving may earn the user a silver medal and two hours of consecutive undistracted driving may earn the driver a gold medal. The user may then accumulate multiple badges, achievements, honors, or trophies for accumulated points in the score or if the score has exceeded incremental predetermined thresholds.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine in the method of Wray, Copeland and Uehara, generating a graphic that indicates meeting or crossing the crossed threshold among other thresholds as taught by Scholl because it would “provide customized incentive mechanisms to users to elicit safer driving behavior patterns” (Scholl, [0017]).
Claim 13: The combination of Wray, Copeland and Uehara discloses the claimed invention as applied to claim 10 above. Wray, Copeland and Uehara do not expressly disclose the following limitations but Scholl teaches wherein generating the digital token comprises: generating a graphic that (1) illustrates a plurality of thresholds indicating different levels of user achievement, the plurality of thresholds including the crossed threshold, and (2) indicates the user meeting or crossing the crossed threshold (see [0044]: The score presented to the user may also include badges, achievements, honors, or trophies if the score is determined to be above a certain threshold. For example, an hour of consecutive undistracted driving may earn the user a silver medal and two hours of consecutive undistracted driving may earn the driver a gold medal. The user may then accumulate multiple badges, achievements, honors, or trophies for accumulated points in the score or if the score has exceeded incremental predetermined thresholds).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine in the system and method of Wray, Copeland and Uehara, generating a graphic that indicates meeting or crossing the crossed threshold among other thresholds as taught by Scholl because it would “provide customized incentive mechanisms to users to elicit safer driving behavior patterns” (Scholl, [0017]).
Claims 15 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Scholl et al (US 2020/0074492 A1) in view of Copeland.
Claim 15: Scholl discloses a method for generating feedback to a user of autonomous vehicles, the method comprising (see [0042]):
aggregating data collected by one or more sensors mounted on or in one or more autonomous vehicles that serviced a plurality of users (see [0021]: the vehicle includes autonomous or semi-autonomous technology or functionality to enable biometric identification. Biometric data may be collected by sensors, such as biometric sensors (e.g., biometric input devices) on the vehicle. [0033]: In some embodiments, driving data associated with the driver's driving characteristics includes data received from vehicle sensors monitoring the state of the driver's user computing device during a trip. );
finding different patterns based on the aggregated data (see [0044]: For example, an hour of consecutive undistracted driving may earn the user a silver medal and two hours of consecutive undistracted driving may earn the driver a gold medal;
associating the different patterns to different digital tokens (see [0044]: For example, an hour of consecutive undistracted driving may earn the user a silver medal and two hours of consecutive undistracted driving may earn the driver a gold medal);
matching data specific to the user to the different patterns; and in response to the data matching a pattern, causing a digital token corresponding to the pattern to be output to the user on a user device (see [0044]: The score presented to the user may also include badges, achievements, honors, or trophies if the score is determined to be above a certain threshold. [0114] In the example embodiment, method 800 includes receiving 802 sensor data. The sensor data is retrieved from a plurality of sensors 120 associated with vehicle 205. Method 800 includes determining 804 a driver activity. The determination is based on data received from sensors 120. Using the driver activity, a score for the driver is calculated 806. Method 800 includes retrieving 808 a driver profile associated with the driver of vehicle 205. Using the score and the driver profile, an incentive is generated 810 for the driver.).
Scholl discloses the user being a driver of an autonomous vehicle. The sole difference between Scholl and the claimed subject matter is that Scholl does not disclose the user being a user of a ride hail and/or delivery services but Copeland which also discloses a method of awarding a user of an autonomous vehicle with a reward for completing tasks, discloses a method of generating feedback to a user of ride hail and/or delivery services (see col. 6 lines 40-43: route that uses the AV to drive the user from the pickup location to the destination location along the most direct and fastest route from the pickup location to the destination location, taking into consideration current traffic conditions. col. 7 lines 30-50: The example gamification module 208 can provide tasks for the user to perform for rewards points, based on user preferences, when the user is riding in the AV. The user can earn reward points for completing each activity and can earn bonus rewards points for completing all activities).
Since each individual element and its function are shown in the prior art, albeit shown in separate reference, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself- that is in the substitution of the user of ride hail of Copeland for the driver of Scholl. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
While Scholl and Copeland disclose conditions for a user to earn rewards. Scholl and Copeland do not explicitly disclose the pattern as being an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme. However, the examiner asserts that the type of pattern as being an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme is simply a label for the data and adds little, if anything, to the claimed acts or steps and thus does not serve to distinguish over the prior art. Any differences related merely to the meaning and information conveyed through labels (i.e., the specific type of pattern) which does not explicitly alter or impact the steps of the method does not patentably distinguish the claimed invention from the prior art in terms of patentability.
Therefore, it would have been obvious to a person of ordinary skill in the art at the time the invention was made to have an operation performed by an autonomous vehicle that serviced the user, the autonomous vehicle identified by a unique name or by a collective set of autonomous vehicles whose unique names share a common theme be included in the reward conditions of Scholl combined with Copeland because the type of criteria does not functionally alter or relate to the steps of the method and merely labeling the criteria differently from that in the prior art does not patentably distinguish the claimed invention.
Scholl and Copeland do not expressly disclose dispatching another autonomous vehicle to the user but Uehara which also discloses an autonomous vehicle service teaches, dispatching another autonomous vehicle to the user (see [0039]: autonomous driving vehicle falls into an undrivable condition, the dispatch device 2 can dispatch an unfilled vehicle so that an occupant riding in the autonomous driving vehicle can get into another autonomous driving vehicle without delay).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine Scholl and Copeland with the method of dispatching another autonomous vehicle to the user as taught by Uehara because it would enable an occupant “get into another autonomous driving vehicle without delay” (Uehara, [0039]).
Claim 18: The combination of Scholl, Copeland and Uehara discloses the claimed invention as applied to claim 15 above. Scholl further discloses, wherein the patterns correspond to different templates, and the templates define one or more conditions or criteria of user achievement (see [0044]).
Claim 19: The combination of Scholl, Copeland and Uehara discloses the claimed invention as applied to claim 15 above. Scholl further discloses, wherein the patterns correspond to different thresholds, and thresholds are numerical values indicating levels of user achievement. (see [0044]: For example, an hour of consecutive undistracted driving may earn the user a silver medal and two hours of consecutive undistracted driving may earn the driver a gold medal. The user may then accumulate multiple badges, achievements, honors, or trophies for accumulated points in the score or if the score has exceeded incremental predetermined thresholds).
Claim 20: The combination of Scholl, Copeland and Uehara discloses the claimed invention as applied to claim 15 above. Scholl further discloses, wherein the patterns correspond to different thresholds, and thresholds are numerical values indicating levels of user achievement on a scale (see [0044]:. The user may then accumulate multiple badges, achievements, honors, or trophies for accumulated points in the score or if the score has exceeded incremental predetermined thresholds). .
Claims 16 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Scholl/Copeland/Uehara as applied to claim 10 above, and further in view of Hinduja et al (US 2022/0068044 A1).
Claim 16: The combination of Scholl, Copeland and Uehara discloses the claimed invention as applied to claim 15 above. Scholl, Copeland and Uehara do not expressly disclose the following limitations but Hinduja wherein finding the different patterns comprises: performing clustering on the aggregated data to identify a plurality of classes of users; determining defining characteristics associated with each class of users; and linking the defining characteristics of the classes of users to the different patterns (see [0025]: first driver behavioral data associated with each of the plurality of drivers A-D. The application server 116 may be configured obtain a plurality of features based on the first maintenance data, the first booking data, the first vehicle data, and the first driver behavioral data. The plurality of features are indicators of driver performance. [0027]: feature values of the plurality of feature values that are indicators of good driver performance are segregated into a first cluster. Similarly, those feature values that are indicators of average driver performance are segregated into a second cluster and the remaining feature values are segregated into a third cluster to indicate bad (or substandard) driver performance. The application server 116 may label each cluster based on a driver performance indicated thereby. [0056]: The machine learning engine 208 may segregate the plurality of feature values 216 into the plurality of clusters 218 based on one or more clustering algorithms).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Scholl, Copeland and Uehara’s driver score with the method of performing clustering on the aggregated data to identify a plurality of classes of users; determining defining characteristics associated with each class of users; and linking the defining characteristics of the classes of users to the different patterns as taught by Hinduja because it would improve understanding of driver's behavior towards the vehicle and a transportation service provider and penalizing and incentivizing the driver based on the driver score ensures a responsible behavior from the driver (Hinduja, [0016]).
Claim 17: The combination of Scholl, Copeland and Uehara discloses the claimed invention as applied to claim 15 above. Scholl, Copeland and Uehara do not expressly disclose the following limitations but Hinduja teaches, wherein finding different patterns comprises training a model using labeled data that associates data collected by the one or more sensors to different classes of users; and matching the data specific to the user comprises providing the data specific to the user as input to the trained model and observing an output of the trained model (see [0029]: The application server 116 may be configured to provide the first dataset as an input to the trained classifier to determine a driver score of the first driver of the first vehicle. The application server 116 is configured to determine the driver score for the first driver based on an output of the trained classifier. The driver score of the first driver may be indicative of a performance and a profitability of the first driver. ).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Scholl, Copeland and Uehara’s driver score with the method of training a model using labeled data that associates data collected by the one or more sensors to different classes of users; and matching the data specific to the user comprises providing the data specific to the user as input to the trained model and observing an output of the trained model as taught by Hinduja because it would improve understanding of driver's behavior towards the vehicle and a transportation service provider and penalizing and incentivizing the driver based on the driver score ensures a responsible behavior from the driver (Hinduja, [0016]).
Response to Arguments
Applicant's arguments regarding the 35 USC 101 rejections have been fully considered but they are not persuasive.
Applicant argues that, “When analyzed correctly, the character of amended Claim 1 as a whole is directed to a specific, technological method for providing enhanced user feedback within an autonomous vehicle (AV) service environment. This method involves the unique identification of AVs and their specific operational feats and culminates in the direct control and initiation of physical AV fleet actions as an integral part of the feedback process. Such a process is intrinsically tied to the sophisticated control and operation of AV systems and their supporting infrastructure and, notably, cannot be practically performed in the human mind.” However, the examiner respectfully disagrees with the Applicant. The claim limitations merely describe the ty