DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This is a non-final office action on the merits. Claims 1-2, 4-6, 8-17, and 19-23 are currently pending and are addressed below.
The examiner notes that the fundamentals of the rejection are based on the broadest reasonable interpretation of the claim language. Applicant is kindly invited to consider the reference as a whole. References are to be interpreted as by one of ordinary skill in the art rather than as by a novice. See MPEP 2141. Therefore, the relevant inquiry when interpreting a reference is not what the reference expressly discloses on its face but what the reference would teach or suggest to one of ordinary skill in the art.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 02/12/2026 has been entered.
Response to Arguments
Applicant's arguments regarding the rejection of claims 1-2, 4-6, 8-17, and 19-22 have been fully considered but they are not persuasive. Specifically, it is challenged that the steps of amended claim 1 reciting, "receiving, by a computing device from a user device, information relating to a destination from a user,” “selecting, based on tracked movements of a plurality of user devices, a preferred parking location from the set of potential parking locations" and "sending information relating to the preferred parking location to the user." Applicant states that the claimed steps cannot be practically performed within a human's mind (see remarks dated 02/12/2026, pg.3). The examiner would like to begin by noting that the standard for a mental process is not whether it is practical for a human to perform, but whether the steps could be performed mentally, or with pen and paper. Computational complexity and incorporation of generic components does not remove something from the mental process category.
The identified step of amended claim one reciting, “selecting,” which under its broadest reasonable interpretation suggests that the computing device chooses the best parking location based on the obtained crowdsource data indicative of other users parking at the same location, or plurality of locations being observed. Arguably, the process of selecting could easily be performed by an individual after some examination of the provided crowdsourced data and reliability indicia associated with other users. In the context of the claim, the “tracked movements of a plurality of user devices,” is simply information regarding behavior of other users in the parking environment that infer which parking locations were commonly used, for instance. At most, the selecting step only uses data as input for decision making. The additional elements of “receiving” and “sending” are recited at a high level of generality and amount of extra-solution activities. The receiving step indicates a general means of receiving, obtaining, or acquiring some form of data gathered from generic computer components like a sensor system, or database. “Sending the information” is also recited at a high level of generality, where the judgement, or determination is provided as an output to the user via a display device, or the like. After careful consideration, there is no unique implementation of using a computing device (i.e., a computer) to incorporate these steps. As such, the examiner respectfully disagrees.
Applicant’s arguments with respect to the rejection of claims 1-2, 4-6, 8-17, and 19-23 under 35 U.S.C 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 1-2, 4-6, 8-17, and 19-23 are rejected under 35 U.S.C. 101 because the claimed
invention is directed to an abstract idea without significantly more.
Step 1
Claims 1, 10, and 17 are directed towards a method, therefore, the claims are within at least one of the four statutory categories.
Step 2A Prong 1
Claim 1:
A method comprising:
receiving, by a computing device from a user device information relating to a destination of a user
determining, by the computing device, based on receiving the information a set of potential parking locations
selecting, based on tracked movements of a plurality of user devices, a preferred parking location from the set of potential parking locations, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination
sending, to the user device, information relating to the preferred parking location to the user.
The examiner submits that the foregoing bolded limitation constitutes a mental process
because under its broadest reasonable interpretation, the claim covers performance of the
limitations in the human mind. The “determining” and “selecting,” steps which under broadest reasonable interpretation suggest that the computing device choose the best parking location based on the obtained crowdsource data indicative of other users parking at the same location, or plurality of locations being observed. The “selecting” step is equivalent to individual making a form of determination, or inference after some examination of the provided crowdsourced data and reliability indicia associated with other users. The “tracked movements of a plurality of user devices,” is simply information regarding behavior of other users in the parking environment that infer which parking locations were commonly used, for instance As such, claim 1 recites a mental process.
Claim 10
A method comprising:
sending, by a user device to a server, information relating to a destination
receiving, by the user device from the server, a set of potential parking locations
selecting, based on tracked movements of a plurality of user devices, a preferred parking location from the set of potential parking locations, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination
sending, by the user device to the server, the preferred parking location
outputting, by the user device and based on data received in response to the sending the preferred parking location, a route to the preferred parking location.
Similar to the analysis of claim 1, the examiner submits that the foregoing bolded limitation constitutes a mental process because under its broadest reasonable interpretation, the claim covers performance of the limitations in the human mind. The “selecting” step is equivalent to individual making a form of determination, or inference after some examination of the provided crowdsourced data and reliability indicia associated with other users. The “tracked movements of a plurality of user devices,” is simply information regarding behavior of other users in the parking environment that infer which parking locations were commonly used, for instance As such, claim 10 recites a mental process.
Claim 17
A method comprising:
receiving, by a computing device from a user device, information relating to a destination
receiving, by the computing device, parking locations data proximate to the destination;
determining, by the computing device, based on data from a database of crowdsourced information, and from the parking locations proximate to the destination, a set of
determining, by the computing device, a preferred parking location from the potential parking locations
sending, to the user device, information relating to the preferred parking location
The examiner submits that the foregoing bolded limitation constitutes a mental process
because under its broadest reasonable interpretation, the claim covers performance of the
limitations in the human mind. The “determining” and “selecting,” steps which under broadest reasonable interpretation suggest that the computing device choose the best parking location based on the obtained crowdsource data indicative of other users parking at the same location, or plurality of locations being observed. The “selecting” step is equivalent to individual making a form of determination, or inference after some examination of the provided crowdsourced data and reliability indicia associated with other users. The “tracked movements of a plurality of user devices,” is simply information regarding behavior of other users in the parking environment that infer which parking locations were commonly used, for instance As such, claim 17 recites a mental process.
Step 2A Prong 2
Claim 1:
A method comprising:
receiving, by a computing device from a user device information relating to a destination of a user
determining, by the computing device, based on receiving the information a set of potential parking locations
selecting, based on tracked movements of a plurality of user devices, a preferred parking location from the set of potential parking locations, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination
sending, to the user device, information relating to the preferred parking location to the user.
The examiner submits that the above identified additional limitations do not integrate the
previously discussed abstract idea into a practical application. Regarding the additional
limitations of, “receiving,” and “sending,” the examiner submits that these limitations are insignificant extra-solution activities that merely use the generic computer components to perform the processes. The “receiving,” step is recited at a high level of generality (i.e. as a general means of receiving, obtaining, or acquiring information for use in a store and processing step) and amounts to mere data gathering, which is a form of insignificant extra solution activity. Additionally, the “send” step is recited at a high level of generality (i.e. as a general means of transmitting, outputting information) and amounts to mere post solution action, which is a form of insignificant extra-solution activity. Thus, it is clear that the abstract ideas have not been integrated into a practical application.
Claim 10
A method comprising:
sending, by a user device to a server, information relating to a destination
receiving, by the user device from the server, a set of potential parking locations
selecting, based on tracked movements of a plurality of user devices, a preferred parking location from the set of potential parking locations, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination
sending, by the user device to the server, the preferred parking location
outputting, by the user device and based on data received in response to the sending the preferred parking location, a route to the preferred parking location
The examiner submits that the above identified additional limitations do not integrate the
previously discussed abstract idea into a practical application. Regarding the additional
limitations of, “sending,” “receiving,” and “outputting,” the examiner submits that these limitations are insignificant extra-solution activities that merely use the generic computer components to perform the processes. The “receiving,” step is recited at a high level of generality (i.e. as a general means of receiving, obtaining, or acquiring information for use in a store and processing step) and amounts to mere data gathering, which is a form of insignificant extra solution activity. Additionally, the “sending” and “outputting” steps are recited at a high level of generality (i.e. as a general means of transmitting, outputting information) and amounts to insignificant extra-solution activities. Thus, it is clear that the abstract ideas have not been integrated into a practical application.
Claim 17
A method comprising:
receiving, by a computing device from a user device, information relating to a destination
receiving, by the computing device, parking locations data proximate to the destination;
determining, by the computing device, based on data from a database of crowdsourced information, and from the parking locations proximate to the destination, a set of potential parking locations, wherein the data from the database of crowdsourced information comprises tracked movements of a plurality of user devices, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination
determining, by the computing device, a preferred parking location from the potential parking locations
sending, to the user device, information relating to the preferred parking location
The examiner submits that the above identified additional limitations do not integrate the
previously discussed abstract idea into a practical application. Regarding the additional
limitations of, “receiving” and “sending,” the examiner submits that these limitations are insignificant extra-solution activities that merely use the generic computer components to perform the processes. The “receiving,” steps are recited at a high level of generality (i.e. as a general means of receiving, obtaining, or acquiring information for use in a store and processing step) and amounts to mere data gathering, which is a form of insignificant extra solution activity. Additionally, the “sending” step is recited at a high level of generality (i.e. as a general means of transmitting, outputting information) and amounts to mere post solution action, which is a form of insignificant extra-solution activity. Thus, it is clear that the abstract ideas have not been integrated into a practical application.
Step 2B
Claim 1, 10, and 17 do not include additional elements (considered both individually and
as an ordered combination) that are sufficient to amount to significantly more than the judicial
exception for the same reasons to those discussed above. The additional elements such as a
processor and memory to perform the step amounts to nothing more than applying the exception
using a generic computer component. General application of an exception using a generic
computer component cannot provide an inventive concept.
Thus, since claims 1, 10, and 17 are: (a) directed towards an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that claims 1, 10, and 17 are directed towards non-statutory subject matter.
Similarly, the dependent claims do not recite any further limitations that cause the claim to be patent eligible. Much like claims 1, 10, and 17 the limitations of these claims are directed towards additional aspects of the judicial exception and/or additional elements that do not integrate the judicial exception into a practical application.
Regarding some of the other examples of additional limitations in the remaining dependent claims such as, “selecting potential parking locations,” (claim 2), “determining the set of potential parking locations,” (claim 9), “determining a first preferred parking” (claim 14), “determining the first preferred parking location,” (claim 16), and “determining the directions to the preferred parking,” (claim 19) the examiner submits that these limitations are additional abstract ideas that can be practically performed in the human mind. For example, the “determining” and “selecting” steps are equivalent to a person perceiving, or looking at the received information relating to a destination from a user and forming a simple judgement of a preferred parking location based on the data either mentally or using a pen and paper.
Additionally, some examples of limitations in the dependent claims that do not recite
additional elements that integrate the judicial exception into a practical application include, “receiving parking data,” (claim 4), “sending the set of potential parking locations,” (claim 7), “receiving data associated with the first preferred parking,” (claim 10), “sending one or more destination specific questions,” (claim 12), and receiving one or more answers,” (claim 16) and are insignificant extra-solution activities. For example, the “receive,” steps are recited at a high level of generality (i.e. as a general means of receiving, obtaining, or acquiring information for use in a store and processing step) and amounts to mere data gathering, which is a form of insignificant extra solution activity. Thus, it is clear that the abstract ideas have not been integrated into a practical application.
As such, claims 1-2, 4-17, and 19-23 are rejected under 35 U.S.C 101 as being drawn to an abstract idea without significantly more, and thus are ineligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 4-6, 8-15, 17, and 19-23 are rejected under 35 U.S.C. 103 as being unpatentable over Ghose Shiva et al. (US201800304926A1), hereinafter referred to as Shiva in view of Myers Charles et al. (US20170132541A1), hereinafter referred to as Charles.
Regarding claim 1, Shiva discloses: a method (see at least Shiva, ¶¶ [0005]) comprising:
receiving, by a computing device, information relating to a destination from a user (see at least Shiva, ¶¶ [0063]-[0065] which discloses receiving information, input as to a desired destination for the current vehicle ride, relating to a destination from a user)
determining, by a computing device, based on receiving the information, and by correlating historical parking data, from a database of crowdsourced information, with parking locations proximate to the destination, a set of potential parking locations (see at least Shiva, ¶¶ [0005]-[0010], [0055]-[0056], [0069]-[0070], [0077] which discloses a determination made that limits and identifies a set of possible parking locations as a result of accessing stored information involving the stored roadway, impediments (construction), and hazard information impacting routing and parking availability relative to this information, this means determining, by a computing device, based on receiving the information, and by correlating historical parking data, from a database of crowdsourced information, with parking locations proximate to the destination, a set of potential parking locations)
Shiva is silent on, however, in the same field of endeavor, Charles discloses:
selecting, based on tracked movements of a plurality of user devices, a preferred parking location from the set of potential parking locations, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination (see at least Charles, Fig.4A, which discloses a crowd-sourced parking area recommendation system; ¶¶ [0005]-[0007], [0011], [0018]-[0020], [0022] discloses a crowd-sourced parking area recommendation system that draws data from other drivers reporting on similar parking area locations, analyzing an indicia of accuracy, and based on the conditions, generating/selecting a parking area based on the crowdsourced data; crowdsourced data may be non-personally identifiable data such as location information, geographic coordinate data (e.g., latitude/longitude), timestamp data, heading information, and floating car data, etc., sourced from other drivers, this means that the tracked movements indicate a plurality of parking locations that were associated by a plurality of users at one or more destinations)
sending, to the user device, information relating to the preferred parking location (see at least Charles, ¶¶ [0022]-[0023], [0025] discloses communicating information related to the generated parking location based on crowdsourced data; displayed and reported onto the computing device viewable by the user)
It would have been obvious to a person of ordinary skill in the art to modify Shiva to include selecting, based on tracked movements of a plurality of user devices, a preferred parking location from the set of potential parking locations, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination and sending, to the user device, information relating to the preferred parking location as taught by Charles. The examiner would like to note that the disclosure of Shiva does appear to send information of the preferred parking location that is viewable by the user, however, the data itself is primarily transmitted to the vehicle systems, prioritizing autonomous control of the vehicle instead of user approval of the preferred parking location. For these reasons, the Charles reference has been applied. Incorporating the teachings would create an improvement to the base invention of Shiva, wherein user input related to the preferred parking location can be taken into consideration via obtained crowdsourced data, thus allowing more variance of choice regarding the user’s preferences that may be integrated into the planned path of the vehicle. Additionally, this allows the user to compare parking choices with a bit more reliability and accuracy of spots vouched by other drivers.
Regarding claim 2, Shiva discloses: the method of claim 1, wherein the selecting is further based on popularity scores for the parking locations proximate to the destination, and determining the set of potential parking locations using the popularity score (see at least Shiva, ¶¶ [0095]-[0097] discloses selecting potential parking locations further based on he popularity score, ¶¶ [0005]-[0010], [0055]-[0056], [0069]-[0070], [0077] which discloses a determination made that limits and identifies a set of possible parking locations as a result of accessing stored information involving the stored roadway, impediments (construction), and hazard information impacting routing and parking availability relative to this information, this means determining, by a computing device, based on receiving the information, and by correlating historical parking data, from a database of crowdsourced information, with parking locations proximate to the destination, a set of potential parking locations)
Regarding claim 4, Shiva discloses: the method of claim 1, further comprising:
sending, to the user device, one or more destination-specific questions based on the destination (see at least Shiva, ¶¶ [0068]-[0070] which discloses sending one or more destination specific questions (ability to receive available instructions provided by one or more users of the vehicle as to a requested destination for the vehicle) based on the destination)
receiving, to the user device, one or more answers to the one or more destination specific questions (see at least Shiva, ¶¶ [0070] which discloses the parking location selection module receiving one or more answers to the one or more destination specific questions)
wherein the selecting the preferred parking location is based on at least one of the one or more answers to the one or more destination-specific questions (see at least Shiva, ¶¶ [0079]-[0081] which discloses selecting the preferred parking location is based on one or more answers to the one or more destination specific questions (user input received from other data via the transceiver); [0084] the calculated scores are influenced by user input data providing information related to one or more destination specific questions)
Regarding claim 5, Shiva discloses: the method of claim 1, further comprising:
sending the destination to a parking data server (see at least Shiva, ¶¶ [0077] which discloses sending the destination (map data related to a vehicle’s desired destination) to a parking data server)
receiving, from the parking data server, the set of potential parking locations proximate to the destination (see at least Shiva, ¶¶ [0065], [0072]-[0073], discloses receiving parking location data for the destination; [0013], [0072]-[0073] discloses wherein the parking location data comprises a parking location, a parking location popularity score (respective score); [0068]-[0070], [0097] one or more destination specific questions related to user inputs related to destination of the vehicle)
Regarding claim 6, Shiva discloses: the method of claim 1, wherein the information relating to the destination comprises one or more of an address, a title, or geospatial coordinates (see at least Shiva, ¶¶ [0052] which discloses information relating to a destination relative to geospatial coordinates via a GPS system implemented in the vehicle)
Regarding claim 8, Shiva discloses: the method of claim 4, wherein the one or more destination-specific questions request input regarding preferences associated with one or more of: a parking location cost, availability of electric vehicle charging at a parking location, if a parking location is covered; if a shuttle to a parking location is available; and distance between a parking location and the destination (see at least Shiva, ¶¶ [0085], [0094] which discloses sending and obtaining data regarding user input of one or more destination specific questions wherein the destination specific question comprises one of respective distances)
Regarding claim 9, Shiva discloses: the method of claim 1, wherein determining the set of potential parking locations comprises:
receiving, from a parking data server, parking delay information associated with the set of potential parking locations (see at least Shiva, ¶¶ [0091]-[0092] discloses the parking data comprising a popularity score (respective score calculated) for each of the parking location in the set of potential parking locations)
wherein the parking delay information comprises one or more of: road closure information at the destination, construction delay information at the destination, and accident information at the destination (see at least Shiva, ¶¶ [0093]-[0094] which discloses receiving parking delay information of the set of potential parking locations (exemplary parking situations relative to a parking location and destination involving proximity to moving and/or stationary objects) comprising road closure information (keep-clear zones) in the popularity score for each of the one or more potential parking locations)
determining the set of potential parking location is further based on the parking delay information (see at least Shiva, ¶¶ [0093]-[0094] discloses determining a set of potential parking locations based on popularity scores (respective scores) and parking delay information (cost map) of the potential parking locations)
Regarding claim 10, Shiva discloses: a method comprising:
sending, by a user device, to a server, information relating to a destination (see at least Shiva, ¶¶ [0063]-[0065] which discloses sending and receiving information (input as to a desired destination for the current vehicle ride) relating to a destination from the server)
receiving, by a user device, from the server, a set of potential parking locations (see at least Shiva, ¶¶ [0063]-[0065] which discloses sending and receiving information (input as to a desired destination for the current vehicle ride) relating to a destination from the server; ¶¶ [0005]-[0010], [0055]-[0056], [0069]-[0070], [0077] which discloses a determination made that limits and identifies a set of possible parking locations as a result of accessing stored information involving the stored roadway, impediments (construction), and hazard information impacting routing and parking availability relative to this information, this means determining, by a computing device, based on receiving the information, and by correlating historical parking data, from a database of crowdsourced information, with parking locations proximate to the destination, a set of potential parking locations)
outputting, by the user device and based on data received in response to the sending the preferred parking location a route to the preferred parking location (see at least Shiva, ¶¶ [0084]-[0088] which discloses receiving data associated with the first preferred parking location comprising a route (path) to the preferred parking location; [0095]-[0096] which discloses the preferred parking being selected by the device as well as the path (maneuver) of the vehicle)
Shiva is silent on, however, in the same field of endeavor, Charles teaches: selecting, by the user device, based on tracked movements of a plurality of user devices, input comprising a selection of a preferred parking location from the set of potential parking locations, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination (see at least Charles, Fig.4A, which discloses a crowd-sourced parking area recommendation system; ¶¶ [0005]-[0007], [0011], [0018]-[0020], [0022] discloses a crowd-sourced parking area recommendation system that draws data from other drivers reporting on similar parking area locations, analyzing an indicia of accuracy, and based on the conditions, generating/selecting a parking area based on the crowdsourced data; crowdsourced data may be non-personally identifiable data such as location information, geographic coordinate data (e.g., latitude/longitude), timestamp data, heading information, and floating car data, etc., sourced from other drivers, this means that the tracked movements indicate a plurality of parking locations that were associated by a plurality of users at one or more destinations)
sending, by the user device, to the server, the preferred parking location (see at least Charles, ¶¶ [0022]-[0023], [0025] discloses communicating information related to the generated parking location based on crowdsourced data; displayed and reported onto the computing device viewable by the user)
It would have been obvious to a person of ordinary skill in the art to modify Shiva to include selecting, based on tracked movements of a plurality of user devices, a preferred parking location from the set of potential parking locations, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination and sending, to the user device, information relating to the preferred parking location as taught by Charles. The examiner would like to note that the disclosure of Shiva does appear to send information of the preferred parking location that is viewable by the user, however, the data itself is primarily transmitted to the vehicle systems, prioritizing autonomous control of the vehicle instead of user approval of the preferred parking location. For these reasons, the Charles reference has been applied. Incorporating the teachings would create an improvement to the base invention of Shiva, wherein user input related to the preferred parking location can be taken into consideration via obtained crowdsourced data, thus allowing more variance of choice regarding the user’s preferences that may be integrated into the planned path of the vehicle. Additionally, this allows the user to compare parking choices with a bit more reliability and accuracy of spots vouched by other drivers.
Regarding claim 11, Shiva discloses: the method of claim 10, further comprising receiving parking data that comprises one or more of:
a parking location description, a parking location address, a parking location geospatial coordinates, a parking location popularity, one or more parking location destination specific questions, a destination address, or destination geospatial coordinates (see at least Shiva, ¶¶ [0013], [0072]-[0073] discloses wherein the parking location data comprises a parking location, a parking location popularity score (respective score); [0068]-[0070], [0097] one or more destination specific questions related to user inputs related to destination of the vehicle)
Regarding claim 12, Shiva discloses: the method of claim 10, further comprising:
outputting, to a display of the user device, one or more destination-specific questions based on the destination (see at least Shiva, ¶¶ [0068]-[0070] which discloses sending one or more destination specific questions (ability to receive available instructions provided by one or more users of the vehicle as to a requested destination for the vehicle) based on the destination)
receiving by the user device, input comprising answers to the one or more destination-specific questions (see at least Shiva, ¶¶ [0070] which discloses the parking location selection module receiving one or more answers to the one or more destination specific questions)
wherein the set of potential parking locations is based on the input comprising the answers to the one or more destination-specific questions (see at least Shiva, ¶¶ [0079]-[0081] which discloses selecting the preferred parking location is based on one or more answers to the one or more destination specific questions (user input received from other data via the transceiver); [0084] the calculated scores are influenced by user input data providing information related to one or more destination specific questions)
Regarding claim 13, Shiva discloses: the method of claim 10, wherein sending the information relating to the destination comprises sending one or more of: a name of the destination; geospatial coordinates of the destination; and an address of the destination (see at least Shiva, ¶¶ [0052] which discloses information relating to a destination relative to geospatial coordinates via a GPS system implemented in the vehicle)
Regarding claim 14, Shiva discloses: the method of claim 10, further comprising receiving popularity data of the set of potential parking locations proximate to the destination (see at least Shiva, ¶¶ [0091]-[0092] discloses the parking data comprising a popularity score (respective score calculated) for each of the parking location in the set of potential parking locations) and wherein the method further comprises:
outputting, to a display of the user device, the set of potential parking locations and the popularity data (see at least Shiva, ¶¶ [0013], [0072]-[0073] discloses wherein the parking location data comprises a parking location, a parking location popularity score (respective score); [0068]-[0070], [0097] one or more destination specific questions related to user inputs related to destination of the vehicle)
Regarding claim 15, Shiva discloses: the method of claim 10, further comprising:
determining directions from a current location to the preferred parking location (see at least Shiva, ¶¶ [0076]-[0077] discloses determining directions (map data) from a current location to a preferred parking location; [0080] discloses a path planned corresponding to the preferred parking location and creates a path of movement of the vehicle)
wherein the outputting further comprises outputting a map from the current location to the preferred parking location (see at least Shiva, ¶¶ [0092]-[0094] which discloses creating a map from the current location (map database determining the optimal parking location) to the preferred parking location)
Regarding claim 17, Shiva discloses: a method comprising:
receiving, by a computing device from a user device, information relating to a destination (see at least Shiva, ¶¶ [0063]-[0065] which discloses receiving information (input as to a desired destination for the current vehicle ride) relating to a destination from a user)
receiving, by the computing device, parking locations to the destination (see at least Shiva, ¶¶ [0063]-[0065] which discloses receiving parking location data relating to a destination from a user)
determining, by the computing device, based on data from a database of crowdsourced information, and from the parking locations proximate to the destination, a set of potential parking locations (see at least Shiva, ¶¶ [0005]-[0010], [0069]-[0070][ which discloses determining a set of potential parking locations based on the information provided by the user (a plurality of parking locations proximate the destination) and parking information obtained)
determining, by the computing device, a preferred parking location from the set of potential preferred parking locations (see at least Shiva, ¶¶ [0005]-[0010], [0055]-[0056], [0069]-[0070], [0077] which discloses a determination made that limits and identifies a set of possible parking locations as a result of accessing stored information involving the stored roadway, impediments (construction), and hazard information impacting routing and parking availability relative to this information, this means determining, by a computing device, based on receiving the information, and by correlating historical parking data, from a database of crowdsourced information, with parking locations proximate to the destination, a set of potential parking locations)
Shiva is silent on, however, in the same field of endeavor, Charles teaches:
wherein the data from the database of crowdsourced information comprises tracked movements of a plurality of user devices, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination (see at least Charles, Fig.4A, which discloses a crowd-sourced parking area recommendation system; ¶¶ [0005]-[0007], [0011], [0018]-[0020], [0022] discloses a crowd-sourced parking area recommendation system that draws data from other drivers reporting on similar parking area locations, analyzing an indicia of accuracy, and based on the conditions, generating/selecting a parking area based on the crowdsourced data; crowdsourced data may be non-personally identifiable data such as location information, geographic coordinate data (e.g., latitude/longitude), timestamp data, heading information, and floating car data, etc., sourced from other drivers, this means that the tracked movements indicate a plurality of parking locations that were associated by a plurality of users at one or more destinations)
sending, to the user device, information relating to the preferred parking location (see at least Charles, ¶¶ [0022]-[0023], [0025] discloses communicating information related to the generated parking location based on crowdsourced data; displayed and reported onto the computing device viewable by the user)
It would have been obvious to a person of ordinary skill in the art to modify Shiva to include selecting, based on tracked movements of a plurality of user devices, a preferred parking location from the set of potential parking locations, wherein the tracked movements indicate a plurality of parking locations that were associated, by a plurality of users of the plurality of user devices, with the destination and sending, to the user device, information relating to the preferred parking location as taught by Charles. The examiner would like to note that the disclosure of Shiva does appear to send information of the preferred parking location that is viewable by the user, however, the data itself is primarily transmitted to the vehicle systems, prioritizing autonomous control of the vehicle instead of user approval of the preferred parking location. For these reasons, the Charles reference has been applied. Incorporating the teachings would create an improvement to the base invention of Shiva, wherein user input related to the preferred parking location can be taken into consideration via obtained crowdsourced data, thus allowing more variance of choice regarding the user’s preferences that may be integrated into the planned path of the vehicle. Additionally, this allows the user to compare parking choices with a bit more reliability and accuracy of spots vouched by other drivers.
Regarding claim 19, Shiva discloses: the method of claim 17, further comprising:
determining directions to the preferred parking location from a current location (see at least Shiva, ¶¶ [0076]-[0077] discloses determining directions (map data) from a current location to a preferred parking location; [0080] discloses a path planned corresponding to the preferred parking location and creates a path of movement of the vehicle)
determining directions from the preferred parking location to the destination and wherein the information relating to the preferred parking location comprises: one or both of the directions to the preferred parking location from the current location and the directions from the preferred parking location to the destination (see at least Shiva, ¶¶ [0092]-[0094] which discloses creating a map from the current location (map database determining the optimal parking location) to the preferred parking location)
Regarding claim 20, Shiva discloses: the method of claim 17, further comprising:
receiving, from a parking data server, delay information of the parking locations proximate to the destination, where the delay information comprises one or more of: road closure information at the destination, construction delay information at the destination, or accident information at the destination; safe passage information to the destination (see at least Shiva, ¶¶ [0093]-[0094] which discloses receiving parking delay information of the set of potential parking locations (exemplary parking situations relative to a parking location and destination involving proximity to moving and/or stationary objects) comprising road closure information (keep-clear zones) in the popularity score for each of the one or more potential parking locations)
determining the set of preferred parking locations is further based on the delay information of the parking locations proximate to the destination (see at least Shiva, ¶¶ [0093]-[0094] discloses determining a set of potential parking locations based on popularity scores (respective scores) and parking delay information (cost map) of the potential parking locations)
Regarding claim 21, the method of claim 1, further comprising: receiving, from the user device, indications of one or more user preferences associated with parking, wherein the determining the set of potential parking locations is further based on the one or more user preferences (see at least Shiva, ¶¶ [0065], [0069]-[0070], [0076]-[0077], which discloses receiving, from the user device, indications of one or more user preferences associated with parking, wherein the determining the set of potential parking locations is further based on the one or more user preferences)
Regarding claim 22, Shiva discloses: the method of claim 10, further comprising:
receiving, by the user device from a second server, historical parking data and wherein the determining the preferred location is further based on correlating the historical parking data with the set of potential parking locations proximate to the destination (see at least Shiva, ¶¶ [0005]-[0010], [0055]-[0056], [0069]-[0070], [0077] which discloses a determination made that limits and identifies a set of possible parking locations as a result of accessing stored information involving the stored roadway, impediments (construction), and hazard information impacting routing and parking availability relative to this information, this means receiving, by the user device from a second server, historical parking data and wherein the determining the set of potential parking locations is further based on correlating the historical parking data with the parking locations proximate to the destination)
Regarding claim 23, Shiva is silent on, however, in the same field of endeavor, Charles teaches: the method of claim 1, further comprising:
determining respective routes, corresponding to the tracked movements, from each of the plurality of parking locations to the destination, wherein the selecting the preferred parking location is based on the route from the preferred parking location to the destination (see at least Charles, Fig.4A, which discloses a crowd-sourced parking area recommendation system; ¶¶ [0005]-[0007], [0011], [0018]-[0020], [0022] discloses a crowd-sourced parking area recommendation system that draws data from other drivers reporting on similar parking area locations, analyzing an indicia of accuracy, and based on the conditions, generating/selecting a parking area based on the crowdsourced data; crowdsourced data may be non-personally identifiable data such as location information, geographic coordinate data (e.g., latitude/longitude), timestamp data, heading information, and floating car data, etc., sourced from other drivers, this means that the tracked movements indicate a plurality of parking locations that were associated by a plurality of users at one or more destinations; [0023]-[0025] discloses determining respective routes corresponding to the tracked movements, from each of the plurality of parking locations to the destination, wherein the selecting the preferred parking location is based on the route from the preferred parking location to the destination)
It would have been obvious to a person of ordinary skill in the art to modify Shiva to include determining respective routes, corresponding to the tracked movements, from each of the plurality of parking locations to the destination, wherein the selecting the preferred parking location is based on the route from the preferred parking location to the destination as taught by Charles. Incorporating the teachings would create an improvement to the base invention of Shiva, wherein user input related to the preferred parking location can be taken into consideration via obtained crowdsourced data, thus allowing more variance of choice regarding the user’s preferences that may be integrated into the planned path of the vehicle. Additionally, this allows the user to compare parking choices with a bit more reliability and accuracy of spots vouched by other drivers.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over modified Shiva in view of Iwuchukwu Tochukwu et al. (US201400278081A1), hereinafter referred to as Tochukwu.
Regarding claim 16, modified Shiva is silent on, however in the same field of endeavor, Tochukwu teaches: The method of claim 12, further comprising:
ranking, by the user device, the set of potential parking locations based on the input comprising the answers to the one or more destination-specific questions (see at least Tochukwu, ¶¶ [0023]-[0024] discloses comparing the set of parking locations by ranks of importance (prioritization of one criterion of the point-of-interest) to identify a preferred parking location, one or more destination specific questions (parking duration) based on user input)
It would have been obvious to a person of ordinary skill in the art to further modify Shiva to include ranking, by the user device, the set of potential parking locations based on the second input comprising the answers to the one or more destination-specific questions as taught Tochukwu. The examiner would like to note that the disclosure of modified Shiva appears to receive input to certain questions (criterion) regarding a destination, in order to determine a preferred parking location, however the ranking of criterion in terms of user preference towards certain questions is not as explicitly disclosed. Incorporating the teachings of Tochukwu would allow for an improvement of the base device of modified Shiva, that offers more user customization in terms of their preferences.
Conclusion
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/KIRSTEN JADE M SANTOS/Examiner, Art Unit 3664
/RACHID BENDIDI/Supervisory Patent Examiner, Art Unit 3664