DETAILED ACTION
This Final Office Action is in response to amendments filed 10/1/2025.
Claims 1, 14, and 20 have been amended.
Claims 1-20 are pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/12/2025 has been considered by the examiner.
Response to Arguments
Rejections under 35 U.S.C. 101
On page 10 of the Remarks filed 10/1/2025, the Applicant contends that the claimed techniques cannot be practically performed within a human mind and are not abstract ideas, given that the claimed techniques cause augmentation of the claimed “anonymized mobility data” and the claimed “sensor data” to “generate vehicle data for the vehicle” and “enable anonymized localization for provision of location-based services to a plurality of vehicles.” The Applicant further cites the specification for additional evidence that the claims are directed to patent eligible subject matter.
The Examiner respectfully disagrees. The Examiner is required to establish the broadest reasonable interpretation of the claim as a whole, and limitations from the specification are not read into the claim language. Specifically, based on the plain meaning of the terms in light of the Applicant’s disclosure, the limitation of “anonymized mobility data” is mere data representative of movement that is anonymized, and the limitations of “sensor data” and “vehicle data” are mere data related to a sensor and vehicle, respectively. While the generally recited data pertains to a “sensor” and “vehicle,” no particular, non-generic vehicle-related sensor or controlled vehicle operations are required by the claim language. The limitation of “to enable anonymized localization for provision of location-based services to a plurality of vehicles” defines the use of the claimed encoded generally recited data (i.e. “vehicle data”) and does not require controlled distribution of particular data to a plurality of vehicles. Further, the limitation of “for provision of location-based services to a plurality of vehicles” merely describes how to generally “apply” the otherwise mental judgements in a generic or general-purpose vehicle environment. As discussed in further detail in the rejection of claim 1 under 35 U.S.C. 101 below, the contended limitations do not integrate the abstract idea into a practical application (step 2A prong two) or provide significantly more (step 2B).
On page 12 of Remarks under “Step 2A - Prong One” section, the Applicant contends that the techniques of claim 1 that enable provision of anonymized mobility data via augmentation of “the anonymized mobility data with the sensor data” cannot be performed in the human mind, given that the human mind does not possess any suitable interface to augment “the anonymized mobility data with the sensor data to generate vehicle data for the vehicle” and also “encode the vehicle data in a database to enable anonymized localization for provision of location-based services to a plurality of vehicles.”
The Examiner respectfully disagrees. The “augment” step is merely combining generally recited data with other generally recited data. While the generally recited data pertains to a “sensor” and “vehicle,” no particular vehicle-related sensor or controlled vehicle operations are required by the claim language; therefore, this limitation encompasses a person looking at two sets of data (i.e. anonymized mobility data and sensor data) and adding one set of data to the other (i.e. adding the sensor data to the anonymized data) in order to generate the combined generally recited data (i.e. vehicle data).
The “encode” step has been evaluated as an additional element in step 2A prong two, as discussed in the rejections below. Specifically, the “encode” step is recited at a high level of generality (i.e. as a general storing/encoding of vehicle data in a database) and amounts to post-solution activity, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). No technological details are recited with respect to the database itself. Specifically, when tested per MPEP 2106.05(f)(1), such limitation is interpreted as a result-oriented solution rather than an actual technological improvement. Thus, the database is found not to integrate the abstract idea into a practical application or provide significantly more. The limitation of “for provision of location-based services to a plurality of vehicles” defines a use of the encoded generally recited data and does not require controlled distribution of particular data to a plurality of vehicles. Further, this limitation merely describes how to generally “apply” the otherwise mental judgements in a generic or general-purpose vehicle environment.
On pages 12-13 of Remarks, with respect to the “Mental Process” section, the Applicant contends that the emphasized portions of the claim, including the “obtain” and “augment” steps and the limitation of “to enable anonymized localization for provision of location-based services to a plurality of vehicles” cannot be considered a mental process.
The Examiner respectfully disagrees. The “obtain” step has been evaluated as an additional element in step 2A prong two, as discussed in the rejections below. Specifically, the “obtain” step is recited at a high level of generality (i.e. as a general obtaining of a sequence of location probe data points and sensor data) and amounts to mere data gathering, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “electronic control unit of a vehicle” is a general computer and is merely claimed as a source of the generally recited data; therefore, the “electronic control unit of a vehicle” does not impose meaningful limits on the claim. See MPEP 2106.05(b)(III). Further, defining the sequence of location probe data points as “correspond[ing] to a trajectory and represent[ing] respective locations of the vehicle during the travel of the vehicle along the road network” merely describes the generally recited data and does not require particular, non-generic sensors or vehicle control operations. Responses to the arguments regarding the “augment” step and limitation of “to enable anonymized localization for provision of location-based services to a plurality of vehicles” have been provided in the preceding paragraphs.
The Applicant further contends that the features of claim 1 to anonymize localization for the vehicle cannot be effectively performed in the human mind since a human mind would be incapable of completely forgetting or at least reliably discarding information for the trajectory associated with the vehicle.
The Examiner respectfully disagrees. A mental process is defined by the courts as an abstract idea that “can be performed in the human mind, or by a human using a pen and paper.” The courts do not distinguish between mental processes that are performed entirely performed in the human mind and mental processes that require a human to use a physical aid to perform the claim limitation. See MPEP 2106.04(a)(2)(III). Therefore, the discarding of information for the trajectory may be reasonably performed by a human erasing a particular portion of locations associated with a trajectory drawn by the human.
On page 14 of Remarks, with respect to the “Step 2A - Prong Two” section, the Applicant contends that the alleged abstract idea is integrated into a practical application at least because the claim causes “encod[ing] the vehicle data in a database to enable anonymized localization for provision of location-based services to a plurality of vehicles.”
The Examiner respectfully disagrees. The “encode” step is recited at a high level of generality (i.e. as a general storing/encoding of vehicle data in a database) and amounts to post-solution activity, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). No technological details are recited with respect to the database itself. Specifically, when tested per MPEP 2106.05(f)(1), such limitation is interpreted as a result-oriented solution rather than an actual technological improvement. Thus, the database is found not to integrate the abstract idea into a practical application or provide significantly more. The limitation of “for provision of location-based services to a plurality of vehicles” defines a use of the encoded generally recited data and does not require controlled distribution of particular data to a plurality of vehicles. Further, this limitation merely describes how to generally “apply” the otherwise mental judgements in a generic or general-purpose vehicle environment, as discussed in the above responses.
On pages 15-17 of Remarks, the Applicant contends claim 1 includes a number of features that provide improvements to location-based technologies for vehicles, with reference to cited passages from the Applicant’s specification.
The Examiner respectfully disagrees. A claim whose entire scope can be performed mentally cannot be said to improve computer technology, e.g., gathering and analyzing information using conventional techniques. See MPEP 2106.05(a). The claim language provides only a result-orientated solution and lacks details as to how the computer performed the modifications. See MPEP 2106.05(f). Limitations from the specification are not read into the claim language. Under its broadest reasonable interpretation, claim 1 has been identified as covering performance using mental processes (Step 2A prong one), and the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B), as explained in detail in the rejections under 35 U.S.C. 101 below.
On page 17 of Remarks, with respect to the “step 2B” section, the Applicant contends that the added elements cannot be considered to be well-understood, routine, or known within the industry at least because they do not appear to be taught by the prior art of record.
While new prior art has been applied to teach the amendments filed 10/1/2025, the Applicant misinterprets step 2B. Specifically, a claim becomes eligible under step 2B when it contains an inventive concept that transforms a judicial exception into “significantly more” than the exception itself. In this case, with respect to the Applicant’s disclosure, the background recites the mobility data as being conventionally used for generic maps, and the specification does not provide any indication that the processing circuitry and electronic control unit are anything other than conventional; therefore, the additional elements considered to be insignificant extra-solution activity in step 2A are further determined to be well-understood, routine, and conventional activity in the field in step 2B.
Rejections under 35 U.S.C. 103
On pages 18-20 of Remarks filed 10/1/2025, the Applicant contends that Biswas does not teach the amended claims.
Due to the amendments filed 10/1/2025, Biswas is no longer applied to the contended limitations; therefore, the Applicant’s arguments, with respect to the application of Biswas, are moot because the new ground of rejection does not rely on Biswas.
On page 19 of Remarks, the Applicant contends that Yin does not teach the limitation of “identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, junction behavior corresponding to a junction of the trajectory where two or more turn maneuvers via the road network are possible by the vehicle” (emphasis added).
The Examiner agrees that Yin does not specify that the recorded GPS vehicle trajectories described in ¶0057 are obtained “via an electronic control unit of the vehicle.” However, new references are applied in combination with Yin to teach this amended feature. Specifically, Yin is applied to teach the technique of “identifying junction behavior…corresponding to a junction of the trajectory where two or more turn maneuvers via the road network are possible by the vehicle” based on a sequence of location probe data points similar to those obtained by an electronic control unit of the vehicle of a new primary reference, as discussed in detail below.
On page 19 of Remarks, the Applicant contends that Yin does not teach the amended “identify” steps, and on pages 20-21 of Remarks, the Applicant further contends that Yin does not teach the amended “apply” step.
The Examiner agrees that Yin fails to teach these amended features. New references have been applied to teach these amended features in the rejections below.
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.
101 Analysis of Claim 1
Claim 1. An apparatus comprising processing circuitry and at least one memory including computer program code instructions, the computer program code instructions configured to, when executed by the processing circuity, cause the apparatus to:
obtain (i) a sequence of location probe data points and (ii) sensor data via an electronic control unit of a vehicle and during travel of the vehicle along a road network, wherein the sequence of location probe data points corresponds to a trajectory and represents respective locations of the vehicle during the travel of the vehicle along the road network;
identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, junction behavior corresponding to a junction of the trajectory where two or more turn maneuvers via the road network are possible by the vehicle;
identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a last location probe data point of a first sub-trajectory for the trajectory;
identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a first location probe data point of a second sub-trajectory for the trajectory;
apply, based on a location probe data point correlation between (i) the junction behavior, (ii) the last location probe data point, and (iii) the first location probe data point, a gap placement in the sequence of location probe data points obtained via the electronic control unit of the vehicle to generate at least a first subsequence of the location probe data points and a second subsequence of the location probe data points;
generate anonymized mobility data for the trajectory associated with the vehicle based on the first subsequence of the location probe data points and the second subsequence of the location probe data points,
augment the anonymized mobility data with the sensor data to generate vehicle data for the vehicle; and
encode the vehicle data in a database to enable anonymized localization for provision of location-based services to a plurality of vehicles.
101 Analysis - Step 1: Statutory category - Yes
The claim recites an apparatus. The claim falls within one of the four statutory categories. MPEP 2106.03
101 Analysis - Step 2A Prong one evaluation: Judicial Exception - Yes - Mental processes
The claim is to be analyzed to determine whether it recites subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) mental processes, and/or c) certain methods of organizing human activity.
The Office submits that the foregoing bolded limitations constitute judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the claim covers performance using mental processes.
The claim recites the limitation of identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, junction behavior corresponding to a junction of the trajectory where two or more turn maneuvers via the road network are possible by the vehicle. Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “junction behavior” is data representative of a junction corresponding to a trajectory where two or more turn maneuvers via a road network are possible by a vehicle. The mere possibility of performing a maneuver by a vehicle does not require actual vehicle operation and merely describes the type of data that is identified. The broadest reasonable interpretation of “sequence of location probe data points,” in light of the overall claim and Applicant's disclosure, is data representative of a series of locations. This “identify” step is performed on the generally recited location data as a post-processing step, such that no particular controlled vehicle operations or vehicle-related sensors are required to acquire the sequence of location probe data points.
The recitation of the “electronic control unit of the vehicle” as having obtained the sequence of probe data points is recited at a high level of generality and merely uses a computer (i.e. electronic control unit) as a tool for having obtained generally recited data, which does not preclude the claims from reciting the abstract process when tested per MPEP 2106.04(a)(2)(III)(C)#3. The mere nominal recitation of a “vehicle” as being an object upon which the “electronic control unit” resides does not take the claim limitations out of the mental process grouping.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of “the processing circuitry.” That is, other than reciting “the processing circuitry,” nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for the “processing circuitry” language, the claim encompasses a person looking at data collected (i.e. sequence of location probe data points) and forming a simple observation and evaluation (i.e. identifying junction behavior). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. “processing circuitry”). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of “the processing circuitry” does not take the claim limitations out of the mental process grouping.
The claim recites the limitation of identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a last location probe data point of a first sub-trajectory for the trajectory. Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “a last location probe data point of a first sub-trajectory” is data representative of a location associated with a series of locations. This “identify” step is performed on the generally recited location data as a post-processing step, such that no particular controlled vehicle operations or vehicle-related sensors are required to acquire the sequence of location probe data points.
The recitation of the “electronic control unit of the vehicle” as having obtained the sequence of probe data points is recited at a high level of generality and merely uses a computer (i.e. electronic control unit) as a tool for having obtained generally recited data, which does not preclude the claims from reciting the abstract process when tested per MPEP 2106.04(a)(2)(III)(C)#3. The mere nominal recitation of a “vehicle” as being an object upon which the “electronic control unit” resides does not take the claim limitations out of the mental process grouping.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of “the processing circuitry.” That is, other than reciting “the processing circuitry,” nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for the “processing circuitry” language, the claim encompasses a person looking at data collected (i.e. sequence of location probe data points) and forming a simple observation and evaluation (i.e. identifying a last location probe data point of a first sub-trajectory). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. “processing circuitry”). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of “the processing circuitry” does not take the claim limitations out of the mental process grouping.
The claim recites the limitation of identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a first location probe data point of a second sub-trajectory for the trajectory. Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “a first location probe data point of a second sub-trajectory” is data representative of a location associated with a series of locations. This “identify” step is performed on the generally recited location data as a post-processing step, such that no particular controlled vehicle operations or vehicle-related sensors are required to acquire the sequence of location probe data points.
The recitation of the “electronic control unit of the vehicle” as having obtained the sequence of probe data points is recited at a high level of generality and merely uses a computer (i.e. electronic control unit) as a tool for having obtained generally recited data, which does not preclude the claims from reciting the abstract process when tested per MPEP 2106.04(a)(2)(III)(C)#3. The mere nominal recitation of a “vehicle” as being an object upon which the “electronic control unit” resides does not take the claim limitations out of the mental process grouping.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of “the processing circuitry.” That is, other than reciting “the processing circuitry,” nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for the “processing circuitry” language, the claim encompasses a person looking at data collected (i.e. sequence of location probe data points) and forming a simple observation and evaluation (i.e. identifying a first location probe data point of a second sub-trajectory). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. “processing circuitry”). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of “the processing circuitry” does not take the claim limitations out of the mental process grouping.
The claim recites the limitation of apply, based on a location probe data point correlation between (i) the junction behavior, (ii) the last location probe data point, and (iii) the first location probe data point, a gap placement in the sequence of location probe data points obtained via the electronic control unit of the vehicle to generate at least a first subsequence of the location probe data points and a second subsequence of the location probe data points. Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “gap placement” is data representative of a space between location-related data (i.e. “sequence of location probe data points”). The broadest reasonable interpretation of “a first subsequence” and “a second subsequence,” in light of the overall claim and Applicant's disclosure, is data pertaining to portions of the location-related data (i.e. “location probe data points”). The “apply” step is performed on the generally recited location data as a post-processing step, such that no particular controlled vehicle operations or vehicle-related sensors are required to acquire the sequence of location probe data points.
The recitation of the “electronic control unit of the vehicle” as having obtained the sequence of probe data points is recited at a high level of generality and merely uses a computer (i.e. electronic control unit) as a tool for having obtained generally recited data, which does not preclude the claims from reciting the abstract process when tested per MPEP 2106.04(a)(2)(III)(C)#3. The mere nominal recitation of a “vehicle” as being an object upon which the “electronic control unit” resides does not take the claim limitations out of the mental process grouping.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of “the processing circuitry.” That is, other than reciting “the processing circuitry,” nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for the “processing circuitry” language, the claim encompasses a person looking at data collected (i.e. the sequence of location probe data points, junction behavior, last location probe data point, and first location probe data point) and forming a simple observation and evaluation (i.e. apply a gap placement in the sequence of location probe data points to generate a first and second subsequence). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. “processing circuitry”). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of “the processing circuitry” does not take the claim limitations out of the mental process grouping.
The claim recites the limitation of generate anonymized mobility data for the trajectory associated with the vehicle based on the first subsequence of the location probe data points and the second subsequence of the location probe data points. Based on the plain meaning of the terms in light of the Applicant's disclosure, the limitation of “anonymized mobility data” is data representative of movement that has been anonymized. The limitation of “for the trajectory associated with the vehicle” merely describes the general use of the generated data and does not require any controlled operation of the vehicle. The “generate” step merely generates generally recited data based on other generally recited data.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of “the processing circuitry.” That is, other than reciting “the processing circuitry,” nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for the “processing circuitry” language, the claim encompasses a person looking at data collected (i.e. the first subsequence and second subsequence) and forming a simple observation and evaluation (i.e. generate anonymized mobility data). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. “processing circuitry”). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of “the processing circuitry” does not take the claim limitations out of the mental process grouping.
The claim recites the limitation of augment the anonymized mobility data with the sensor data to generate vehicle data for the vehicle. The “augment” step is merely combining generally recited data with other generally recited data. While the generally recited data pertains to a “sensor” and “vehicle,” no particular vehicle-related sensor or controlled vehicle operations are required by the claim language.
Therefore, this limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of “the processing circuitry.” That is, other than reciting “the processing circuitry,” nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for the “processing circuitry” language, the claim encompasses a person looking at data collected (i.e. anonymized mobility data and sensor data) and forming a simple observation and evaluation (i.e. generate vehicle data). Such observations and evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. “processing circuitry”). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of “the processing circuitry” does not take the claim limitations out of the mental process grouping.
Thus, the claim recites, describes, or sets forth a mental process.
101 Analysis - Step 2A Prong two evaluation: Practical Application - No
The claim is evaluated for whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined potions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”).
The claim recites additional elements of:
obtain (i) a sequence of location probe data points and (ii) sensor data via an electronic control unit of a vehicle and during travel of the vehicle along a road network, wherein the sequence of location probe data points corresponds to a trajectory and represents respective locations of the vehicle during the travel of the vehicle along the road network;
encode the vehicle data in a database to enable anonymized localization for provision of location-based services to a plurality of vehicles.
The “obtain” step is recited at a high level of generality (i.e. as a general obtaining of a sequence of location probe data points and sensor data) and amounts to mere data gathering, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “electronic control unit of a vehicle” is a general computer and is merely claimed as a source of the generally recited data; therefore, the “electronic control unit of a vehicle” does not impose meaningful limits on the claim. See MPEP 2106.05(b)(III). Further, defining the sequence of location probe data points as “correspond[ing] to a trajectory and represent[ing] respective locations of the vehicle during the travel of the vehicle along the road network” merely describes the generally recited data and does not require particular, non-generic sensors or vehicle control operations.
The “encode” step is recited at a high level of generality (i.e. as a general storing/encoding of vehicle data in a database) and amounts to post-solution activity, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). No technological details are recited with respect to the database itself. Specifically, when tested per MPEP 2106.05(f)(1), such limitation is interpreted as a result-oriented solution rather than an actual technological improvement. Thus, the database is found not to integrate the abstract idea into a practical application or provide significantly more.
The limitation of “for provision of location-based services to a plurality of vehicles” defines a use of the encoded generally recited data and does not require controlled distribution of particular data to a plurality of vehicles. Further, this limitation merely describes how to generally “apply” the otherwise mental judgements in a generic or general-purpose vehicle environment.
101 Analysis - Step 2B evaluation: Inventive concept - No
The claim is evaluated for whether the claim as a whole amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the “obtain” and “encode” steps were considered to be insignificant extra-solution activity in Step 2A, and thus, they are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The background recites the mobility data (i.e. location probe data points) as being conventionally used for generic maps, and the specification does not provide any indication that the processing circuitry and electronic control unit are anything other than conventional. MPEP 2106.05(d)(II), and the cases cited therein, including TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016), OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014), but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, indicate that mere receiving or transmitting of data over a network and storing and retrieving information in memory are a well-understood, routine, and conventional functions when claimed in a merely generic manner, as it is here. Thus, the claim is ineligible.
101 Analysis of Dependent Claims 2-13
Dependent claims 2-13 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of the dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application.
Claim 2 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
determine the last location probe data point of a first sub-trajectory based on a first junction probe data point in the junction.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. first sub-trajectory and first junction probe data point in the junction) and forming a simple evaluation (i.e. determine the last location probe data point). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of by the processing circuitry does not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 3 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
randomly determine the last location probe data point of a first sub-trajectory based on a subset of location probe data points prior to a first junction probe data point in the junction.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. first sub-trajectory and first junction probe data point in the junction) and forming a simple evaluation (i.e. determine the last location probe data point). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of by the processing circuitry does not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 4 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
determine the first location probe data point of the second sub-trajectory based on a random selection of probe data points after a last junction probe data point in the junction.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. second sub-trajectory, random selection of probe data points, and last junction probe data point in the junction) and forming a simple evaluation (i.e. determine the first location probe data point). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of by the processing circuitry does not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 5 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
determine the first location probe data point of the second sub-trajectory based on a different junction associated with the sequence of location probe data points.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. second sub-trajectory and different junction) and forming a simple evaluation (i.e. determine the first location probe data point). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of by the processing circuitry does not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 6 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
apply the gap placement after the junction in the sequence of location probe data points.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. junction in the sequence of location probe data points) and forming a simple evaluation (i.e. apply the gap placement). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of by the processing circuitry does not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 7 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
determine one or more features based on a combination of at least two of latitude data associated with the vehicle during capture of one or more location probe data points within the sequence of location probe data points, longitude data associated with the vehicle during capture of one or more location probe data points within the sequence of location probe data points, timestamp data for one or more location probe data points within the sequence of location probe data points, speed data for the vehicle during capture of one or more location probe data points within the sequence of location probe data points, or heading data indicative of a direction of travel associated with the vehicle during capture of one or more location probe data points within the sequence of location probe data points; and
identify the junction behavior based on the one or more features.
The broadest reasonable interpretation of the limitation of “features” is merely data, and the broadest reasonable interpretation of the limitations of “latitude data,” “longitude data,” “timestamp data,” “speed data,” and “heading data” is data pertaining to vehicle-related travel. The claim language does not incorporate particular vehicle sensors and merely utilizes previously-recorded data.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for by the processing circuitry language, with respect to the “determine” step, the claim encompasses a person looking at data collected (i.e. latitude data, longitude data, timestamp data, speed data, and/or heading data) and forming a simple evaluation (i.e. determine features), and with respect to the “identify” step, the claim encompasses a person looking at data collected (i.e. features) and forming a simple evaluation (i.e. identify junction behavior). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of by the processing circuitry does not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 8 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
apply the one or more data features to a machine learning model configured to classify a portion of the sequence of location probe data points as the junction behavior.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. one or more features) and forming a simple evaluation (i.e. classify a portion of the sequence of location probe data points). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III).
Further, the “machine learning model” is used to generally apply the abstract idea without limiting how the machine learning model functions. The machine learning model is described at a high level, such that it amounts to using a computer with a generic machine learning model to apply the abstract idea. The limitation only recites the outcome of “applying” without any details about how the outcomes are achieved.
Therefore, the mere nominal recitations of by the processing circuitry and apply the one or more data features to a machine learning model do not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 9 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
train the machine learning model based on a set of labels associated with junction probe data points and non-junction probe data points.
The “train” step is recited at a high level of generality and amounts to mere instructions to implement the abstract idea on a generic computer. See Example 47 in Federal Register Notice Issued July 2024. Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 10 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
apply the one or more data features to a deterministic model configured to classify a portion of the sequence of location probe data points as the junction behavior.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. For example, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. data features) and forming a simple evaluation (i.e. classify a portion of the sequence of location probe data points). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III).
Further, the “deterministic model” is used to generally apply the abstract idea without limiting how the deterministic model functions. The deterministic model is described at a high level, such that it amounts to using a computer with a generic deterministic model to apply the abstract idea. The limitation only recites the outcome of “applying” without any details about how the outcomes are achieved.
Therefore, the mere nominal recitations of by the processing circuitry and apply the one or more data features to a deterministic model do not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 11 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
configure the deterministic model based on a set of rules associated with junction probe data points and non-junction probe data points.
The “configure” step is recited at a high level of generality and amounts to mere instructions to implement the abstract idea on a generic computer. See Example 47 in Federal Register Notice Issued July 2024. Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 12 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
identify a first portion in the sequence of location probe data points as a potential origin location of the vehicle during a journey associated with the travel of the vehicle along the portion of the road network;
identify the junction behavior in the first portion in the sequence of location probe data points based on one or more features for the sequence of location probe data points; and
apply the gap placement in the first portion in the sequence of location probe data points.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. In regards to the “identify a first portion” step, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. sequence of location probe data points) and forming a simple evaluation (i.e. identify a first portion). In regards to the “identify the junction behavior” step, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. sequence of location probe data points and features) and forming a simple evaluation (i.e. identify the junction behavior). In regards to the “apply” step, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. sequence of location probe data points) and forming a simple evaluation (i.e. apply the gap placement). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of by the processing circuitry does not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Claim 13 recites the limitation of the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
identify a last portion in the sequence of location probe data points as a potential destination location of the vehicle during a journey associated with the travel of the vehicle along the portion of the road network;
identify the junction behavior in the last portion in the sequence of location probe data points based on one or more features for the sequence of location probe data points; and
apply the gap placement in the last portion in the sequence of location probe data points.
This limitation, as drafted, is a simple cognitive process that, under its broadest reasonable interpretation, can be practically covered in the human mind, or by a human using a pen and paper, but for the recitation of by the processing circuitry. That is, other than reciting by the processing circuitry, nothing in the claim elements precludes the step from practically being performed in the mind, or by a human using a pen and paper. In regards to the “identify a last portion” step, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. sequence of location probe data points) and forming a simple evaluation (i.e. identify a last portion). In regards to the “identify the junction behavior” step, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. sequence of location probe data points and features) and forming a simple evaluation (i.e. identify the junction behavior). In regards to the “apply” step, but for by the processing circuitry language, the claim encompasses a person looking at data collected (i.e. sequence of location probe data points) and forming a simple evaluation (i.e. apply the gap placement). Such evaluations are listed as abstract by MPEP 2106.04(a)(2)(III). The courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer (i.e. processing circuitry). See MPEP 2106.04(a)(2)(III). Therefore, the mere nominal recitation of by the processing circuitry does not take the claim limitations out of the mental process grouping.
Based on the tests above, the Examiner finds that the additional elements do not integrate the abstract idea into a practical application (Step 2A prong two) or provide significantly more (Step 2B).
Therefore, dependent claims 2-13 are not patent eligible under the same rationale as provided for in the rejection of independent claim 1.
101 Analysis of Claim 14
Claim 14. A computer-implemented method, comprising:
obtaining (i) a sequence of location probe data points and (ii) sensor data via an electronic control unit of a vehicle and during travel of the vehicle along a road network, wherein the sequence of location probe data points corresponds to a trajectory and represents respective locations of the vehicle during the travel of the vehicle along the road network;
identifying, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, junction behavior corresponding to a junction of the trajectory where two or more turn maneuvers via the road network are possible by the vehicle;
identifying, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a last location probe data point of a first sub-trajectory for the trajectory;
identifying, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a first location probe data point of a second sub-trajectory for the trajectory;
applying, based on a location probe data point correlation between (i) the junction behavior, (ii) the last location probe data point, and(iii) the first location probe data point, a gap placement in the sequence of location probe data points obtained via the electronic control unit of the vehicle to generate at least a first subsequence of the location probe data points and a second subsequence of the location probe data points;
generating anonymized mobility data for the trajectory associated with the vehicle based on the first subsequence of the location probe data points and the second subsequence of the location probe data points;
augmenting the anonymized mobility data with the sensor data to generate vehicle data for the vehicle; and
encoding the vehicle data in a database to enable anonymized localization for provision of location-based services to a plurality of vehicles.
101 Analysis - Step 1: Statutory category - Yes
The claim recites a method including at least one step. The claim falls within one of the four statutory categories. MPEP 2106.03
101 Analysis - Step 2A Prong one evaluation: Judicial Exception - Yes - Mental processes
An analysis similar to that of independent claim 1 is made for independent claim 14, with respect to step 2A prong one.
101 Analysis - Step 2A Prong two evaluation: Practical Application - No
An analysis similar to that of independent claim 1 is made for independent claim 14, with respect to step 2A prong two.
101 Analysis - Step 2B evaluation: Inventive concept - No
An analysis similar to that of independent claim 1 is made for independent claim 14, with respect to step 2B.
Thus, the claim is ineligible.
101 Analysis of Dependent Claims 15-19
Dependent claims 15-19 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of the dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application.
Specifically, claims 15-19 are similar to claims 2-6, respectively, and therefore, the limitations of claims 15-19 represent a mere narrowing of the abstract idea (step 2A prong one) with no additional computer-based elements integrating the abstract idea into a practical application (step 2A prong two) or provide significantly more (step 2B) using analyses similar to those discussed in the rejections of dependent claims 2-6 above.
Therefore, dependent claims 15-19 are not patent eligible under the same rationale as provided for in the rejection of independent claim 14.
101 Analysis of Claim 20
20. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising program code instructions to:
obtain (i) a sequence of location probe data points and (ii) sensor data via an electronic control unit of a vehicle and during travel of the vehicle along a road network, wherein the sequence of location probe data points represents respective locations of the vehicle during the travel of the vehicle along the road network;
identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, junction behavior corresponding to a junction of the trajectory where two or more turn maneuvers via the road network are possible by the vehicle;
identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a last location probe data point of a first sub-trajectory for the trajectory;
identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a first location probe data point of a second sub-trajectory for the trajectory;
apply, based on a location probe data point correlation between (i) the junction behavior,(ii) the last location probe data point, and (iii) the first location probe data point, a gap placement in the sequence of location probe data points obtained via the electronic control unit of the vehicle to generate at least a first subsequence of the location probe data points and a second subsequence of the location probe data points;
generate anonymized mobility data for the trajectory associated with the vehicle based on the first subsequence of the location probe data points and the second subsequence of the location probe data points;
augment the anonymized mobility data with the sensor data to generate vehicle data for the vehicle; and
cause transmission of the anonymized mobility vehicle data to a server computing device.
101 Analysis - Step 1: Statutory category - Yes
The claim recites a product or article of manufacture. The claim falls within one of the four statutory categories. MPEP 2106.03
101 Analysis - Step 2A Prong one evaluation: Judicial Exception - Yes - Mental processes
An analysis similar to that of independent claim 1 is made for independent claim 20, with respect to step 2A prong one.
101 Analysis - Step 2A Prong two evaluation: Practical Application - No
An analysis similar to that of independent claim 1 is made for independent claim 20, with respect to step 2A prong two.
Further, the “cause” step is recited at a high level of generality (i.e. as a general transmission of data) and amounts to post-solution activity, which is a form of insignificant extra-solution activity. See MPEP 2106.05(g). The “server computing device” contributes only nominally or insignificantly to the execution of the claimed method (e.g., in an insignificant extra-solution activity step or in a field-of-use limitation) and is merely an object on which the method operates (e.g., receive anonymized mobility data); therefore, the “server computing device” limitation does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(b). No technological details are recited with respect to the “server computing device” itself. The “server computing device” merely acts in its ordinary capacity for tasks (e.g., to store data), and therefore, does not integrate the abstract idea into a practical application or provide significantly more. See MPEP 2106.05(f)(2).
101 Analysis - Step 2B evaluation: Inventive concept - No
An analysis similar to that of independent claim 1 is made for independent claim 20, with respect to step 2B.
Specifically, under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the “obtain” and “cause” steps were considered to be insignificant extra-solution activity in Step 2A, and thus, they are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The background recites the mobility data (i.e. “location probe data points”) as being conventionally used for generic maps, and the specification does not provide any indication that the computer and sensors are anything other than conventional. MPEP 2106.05(d)(II), and the cases cited therein, including TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016), OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014), but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014), Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, indicate that receiving or transmitting data over a network and storing and retrieving information in memory are well-understood, routine, and conventional functions when claimed in a merely generic manner, as it is here. Thus, the claim is ineligible.
Thus, the claim is ineligible.
Claims 1-20 are thus found ineligible under 35 U.S.C. §101 as directed to an abstract idea, with the additional computer-based elements, as tested above, not integrating the abstract idea into a practical application (Step 2A prong two) or providing significantly more (Step 2B).
Key to Interpreting the Prior Art Rejections
For readability, all claim language has been underlined.
Citations from prior art are provided at the end of each limitation in parentheses.
Any further explanations that were deemed necessary by the Examiner are provided at the end of each claim limitation.
The Applicant is encouraged to contact the Examiner directly if there are any questions or concerns regarding the current Office Action.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-4, 6-17, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Busser (US 2019/0017832 A1), hereinafter Busser, in view of Yin et al. (US 2022/0230450 A1), hereinafter Yin, Dorum (US 2016/0102984 A1), hereinafter Dorum, and Marumoto (US 2009/0318121 A1), hereinafter Marumoto.
Claim 1
Busser discloses the claimed apparatus (see Figure 6, depicting apparatus 100) comprising processing circuitry and at least one memory including computer program code instructions (see ¶0056-0057, regarding apparatus 100 includes different units comprising one or more microprocessors for carrying out the method steps of method 10; ¶0040, regarding that the invention includes a computer program product that is loaded into microprocessor for carrying out the steps of the method), the computer program code instructions configured to, when executed by the processing circuity, cause the apparatus to:
obtain (i) a sequence of location probe data points (i.e. position) and (ii) sensor data (i.e. height) via an electronic control unit of a vehicle and during travel of the vehicle along a road network (see ¶0056, regarding that apparatus 100 includes a capture unit 110 that receives captured routes; ¶0012, regarding a route, defined as spatial movement of an object from a starting point to a destination point via successive waypoints, is recorded via a navigation system belonging to a vehicle, as described in ¶0003; ¶0049, regarding that the waypoints include position indications as well as height indications, defined as being received via a GPS of a navigation system in ¶0003-0004), wherein the sequence of location probe data points corresponds to a trajectory and represents respective locations of the vehicle during the travel of the vehicle along the road network (see ¶0049, with respect to the example in Figure 1, regarding that a first route R1 from starting point S1 to destination point Z1 includes dots that represent waypoints W for which position indications are available).
As specifically described in ¶0042, Figure 1 of Busser is a road map, and therefore, the route R1 may reasonably correspond to “travel of the vehicle along a road network.” Further, the vehicle navigation system of Busser may be reasonably interpreted as an “electronic control unit of a vehicle,” given its known specialized function to process GPS and sensor data for generating various forms of guidance.
Busser further discloses that the claimed apparatus is caused to identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, junction behavior corresponding to a junction of the trajectory where two or more turn maneuvers via the road network are possible by the vehicle (see ¶0056, regarding that capture unit 110 of apparatus 100 determines routes that have at least one waypoint or a partial route of adjacent waypoints in common, which is marked as a segmentation point by the segmentation unit 120; ¶0054, regarding a segmentation point is a waypoint that represents an intersection or T-junction). The limitation of “junction behavior” is interpreted in light of the Applicant’s specification filed 11/28/2022, which defines junction behavior as “correspond[ing] to a junction (e.g., junction geometry, a junction portion, etc.) of the trajectory where multiple maneuvers are possible by the vehicle” in paragraph [0083]. Therefore, the identification of a segmentation point that defines an intersection or T-junction in Busser reasonably teaches the identification of “junction behavior,” interpreted under the broadest reasonable interpretation consistent with the Applicant’s disclosure. In case this feature is not clearly disclosed by Busser, the identification of a junction from location data detected by a vehicle is well known in the art and would be obvious to incorporate into Busser, in light of Yin.
Specifically, Yin teaches the known technique of identify[ing], based on location data obtained from a vehicle’s trajectory 21, where the location data is defined as GPS data in ¶0028 (similar to the sequence of location probe data points obtained via an electronic control unit of the vehicle taught by Busser), junction behavior corresponding to a junction of trajectory 21 (similar to the trajectory taught by Busser) where two or more turn maneuvers via roads depicted in Figure 4 and described in ¶0051-0052 (similar to the road network taught by Busser) are possible by the vehicle (see ¶0031, with respect to Figures 1 and 4, regarding that road intersections are identified from the location data 20 obtained from a vehicle’s trajectory 21).
In Busser, a junction is identified for the removal of waypoints in the region of the junction. In Yin, a junction is identified for mapping applications. However, it is the technique of identifying a junction from a sequence of location probe data points that is modified by Yin; therefore, the particular use of the identified junction does not influence this combination.
Since the systems of Busser and Yin are directed to the same purpose, i.e. obtaining a sequence of location data associated with a vehicle trajectory, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the apparatus of Busser, so as to identify, based on the sequence of location probe data points obtained via the one or more sensors of the vehicle, junction behavior corresponding to a junction of the trajectory where two or more turn maneuvers via the road network are possible by the vehicle, in the same manner that Yin identifies road intersections from the location data obtained from a vehicle’s trajectory, with the predictable result of providing automatic intersection detection (¶0002 of Yin) applicable to desirably preventing reconstruction of the user’s overall route (¶0016 of Busser) by ensuring that turning direction cannot be discerned (¶0024 of Busser).
Busser further discloses that the claimed apparatus is caused to identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a last location probe data point of a first sub-trajectory for the trajectory (see ¶0056, regarding segmentation unit 120 of apparatus 100 segments each route into at least two partial routes, where each partial route includes at least one waypoint as a segmentation point; ¶0023-0024, regarding that waypoints in the region of the segmentation point are removed), and identify, based on the sequence of location probe data points obtained via the electronic control unit of the vehicle, a first location probe data point of a second sub-trajectory for the trajectory (see ¶0056, regarding segmentation unit 120 of apparatus 100 segments each route into at least two partial routes, where each partial route includes at least one waypoint as a segmentation point; ¶0023-0024, regarding that waypoints in the region of the segmentation point are removed). With respect to Figure 3 of Busser, by segmenting a route (e.g., route R1) into partial routes (e.g. partial route R1.3 and partial route R1.2) at a segmentation point (e.g., segmentation point T1) defined as a waypoint at an intersection or T-junction (see ¶0054), such that waypoints in the region of the segmentation point are removed (see ¶0023-0024), a “last location probe data point” may be reasonably taught as a non-removed waypoint associated with partial route R1.2, and a “first location probe data point” may be reasonably taught as a non-removed waypoints associated with partial route R1.3, such that the first and last location probe data points represent the non-removed waypoints between the gap formed by the removed waypoints.
Busser further discloses that the claimed apparatus is caused to apply, based on a location probe data point correlation between (i) the junction behavior, (ii) the last location probe data point and (iii) the first location probe data point, a gap placement in the sequence of location probe data points obtained via the electronic control unit of the vehicle to generate at least a first subsequence of the location probe data points and a second subsequence of the location probe data points (see ¶0056-0057, regarding segmentation unit 120 of apparatus 100 segments each route into at least two partial routes, where each partial route includes at least one waypoint as a segmentation point, and a data record for each partial route is stored in storage unit 130; ¶0023-0024, regarding that waypoints in the region of the segmentation point are removed, and the segmentation point is an intersection or T-junction of roads). The “gap placement” is taught by the region of removed waypoints associated with the segmentation point at a T-junction, e.g., segmentation point T1 in Figure 3.
Busser further discloses that the claimed apparatus is caused to generate anonymized mobility data for the trajectory associated with the vehicle based on the first subsequence of the location probe data points and the second subsequence of the location probe data points (see ¶0056, regarding anonymization unit 150 of apparatus 100 removes object-identifying data before further processing in the capture unit 100, which identifies segmentation points for segmentation into at least two partial routes by segmentation unit 120; ¶0023-0024, regarding that the segmentation point is an intersection or T-junction of a road, where waypoints in the region of the segmentation point are removed, so that the turning direction or selected lane cannot be accurately discerned from the start or end of a partial route). Busser teaches the “anonymized mobility data” as the partial routes, similar to the Applicant’s disclosure that describes “the first subsequence of the location probe data points and the second subsequence of the location probe data points correspond to anonymized mobility data for the vehicle” in at least paragraph [0038] of the specification filed 11/28/2022.
Busser further discloses that the claimed apparatus is caused to augment the anonymized mobility data with the sensor data to generate vehicle data for the vehicle (see ¶0049, regarding that the waypoints include position indications and also time or height indications, where the waypoints in the region of the segmentation point are removed, so that the turning direction cannot be accurately discerned from the start or end of a partial route, as described in ¶0023-0024). The “anonymized mobility data” (i.e. partial routes that include position indications) of Busser is augmented with “sensor data” (i.e. height indications), due to the waypoints that define the partial routes including both position and height indications (see ¶0049) provided from a GPS of the vehicle navigation system (see ¶0003-0004). In case the claimed augmentation is intended to occur after the sequence of location probe data points are obtained, Dorum is applied in combination with Busser to more clearly teach the known alternative technique.
Specifically, similar to Busser, Dorum teaches recording both location and elevation data representative of paths traveled through a geographic area by a mobile device associated with a vehicle (see ¶0027). Dorum further teaches an alternative technique of augmenting mobile data points, e.g., two dimensional position data (similar to the anonymized mobility data taught by Busser) with other data, e.g., elevation data (similar to the sensor data taught by Busser) to generate vehicle data for the vehicle (similar to the vehicle taught by Busser) (see ¶0028, regarding that the mobile device data points are supplemented with other data from other sources, e.g., elevation data, where mobile device data includes location representative of paths traveled through a geographic area by the mobile device associated with a vehicle, as described in ¶0027, with respect to step 230 of Figure 2). Receiving a collection of mobile device data points in step 230, described in ¶0027 of Dorum, implies that after collection of the mobile device data points, individual points are then supplemented to enhance the data quality before further analysis.
The technique of augmenting a sequence of position data that defines a vehicle route taught by Dorum may be reasonably applied to each partial route (i.e. “anonymized mobility data”) of Busser.
Since the systems of Busser and Dorum are directed to the same purpose, i.e. recording a sequence of location points during travel of a vehicle along a road network, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the apparatus of Busser to augment the anonymized mobility data with the sensor data to generate vehicle data for the vehicle, in the same manner that the elevation data of Dorum augments the mobile device data points, with the predictable result of alternatively generating the same combination of position and elevation data of Busser (see ¶0049) by supplementing the position data with data from other sources that may improve the data collected by the mobile device of the vehicle (¶0027-0028 of Dorum).
Busser, as modified by Dorum, further discloses that the claimed apparatus is caused to encode the vehicle data in a database to enable anonymized localization for provision of location-based services to a plurality of vehicles (see ¶0057-0058, regarding that data relating to each waypoint is stored in a data record for each partial route in storage unit 130, which can be output via output unit 140 for conforming to data protection law for evaluation or control, as described in ¶0028; ¶0005, regarding that the recorded routes are useful for providing innovative services, such as traffic jam reports, detecting traffic jams early or avoiding traffic jams). There are no claimed steps in which the encoded vehicle data is disseminated among a plurality of vehicles. The limitation of “for provision of location-based services to a plurality of vehicles” is merely describing a use of the encoded vehicle data.
In case the limitation of “for provision of location-based services to a plurality of vehicles” cannot be reasonably gleaned from Busser, with respect to the output for control in ¶0028 and the use for providing services such as traffic jam reports, detecting traffic jams early and for avoiding traffic jams in ¶0005, Marumoto is applied in combination with Busser to teach this particular use of similarly stored vehicle data.
Specifically, Marumoto teaches GPS 103 associated with driving recorder 1 of a vehicle acquires positional data including latitude, longitude, and altitude, which is recorded as part of the driving condition data for post-analysis of a traveling route, as described in ¶0038 (similar to the vehicle data taught by Busser). Marumoto further teaches that server 6 (similar to the apparatus taught by Busser) receives and stores the driving condition data (see ¶0081-0084, with respect to Figure 4) for provision of location-based services to a plurality of vehicles (see ¶0091, regarding that server 6 transmits driving condition data of a traffic accident location to plural mobile telephone terminals associated with respective vehicles within an area; ¶0086-0087, regarding server 6 transfers latest accumulated traffic accident data to mobile telephone terminal 2 which transfers the latest accumulated traffic accident data to driving recorder 1, defined as mounted in a vehicle in ¶0082-0083; Figure 4, depicting a plurality of vehicles with respective driving recorders).
In Busser, as modified by Dorum, an apparatus records partial routes comprised of a sequence of locations augmented with elevation data. In Marumoto, an apparatus records a sequence of locations and associated altitude data. However, it is the use of a recorded sequence of data points representative of a vehicle route for provision of location-based services to a plurality of vehicles that is modified by Marumoto; therefore, any operations to augment or anonymize the recorded data do not influence this combination.
Since the systems of Busser and Marumoto are directed to the same purpose, i.e. recording a sequence of location points during travel of a vehicle, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the step of encode the vehicle data in a database to enable anonymized localization of Busser to be for provision of location-based services to a plurality of vehicles, in the same manner that a sequence of positions of a vehicle route is recorded in a server in Marumoto for the transmission of driving condition data to plural vehicles within a particular area, with the predictable result of alerting a driver approaching a traffic-accident prone location (¶0087 of Marumoto), so as to encourage the driver to look for an alternative route and avoid road congestion (¶0091 of Marumoto).
Claims 2 and 15
Busser further discloses that the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
determine the last location probe data point of a first sub-trajectory based on a first junction probe data point (i.e. segmentation point) in the junction (see ¶0056, regarding segmentation unit 120 of apparatus 100 segments each route into at least two partial routes, where each partial route includes at least one waypoint as a segmentation point; ¶0054, regarding a segmentation point may be a waypoint that represents intersections or T-junctions; ¶0023-0024, regarding that waypoints in the region of the segmentation point are removed).
See the explanations provided in the rejection of claim 1, with respect to the limitation of “identify…a last location probe data point.”
Claims 3 and 16
Busser further discloses that the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
randomly determine the last location probe data point of a first sub-trajectory based on a subset of location probe data points prior to a first junction probe data point (i.e. segmentation point) in the junction (see ¶0056, regarding segmentation unit 120 of apparatus 100 segments each route into at least two partial routes, where each partial route includes at least one waypoint as a segmentation point; ¶0054, regarding a segmentation point may be a waypoint that represents intersections and T-junctions; ¶0023-0024, regarding that waypoints in the region of the segmentation point are removed).
The “subset of location probe data points” prior to waypoint W1 that defines segmentation point T1 associated with the T-junction depicted in the example of Figure 3 of Busser may be reasonably taught by the waypoints that make up part of the region of the segmentation point that are removed (see ¶0023-0024). The limitation of “random” does not require a certain or particular determination of the last location probe data point.
Claims 4 and 17
Busser further discloses that the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
determine the first location probe data point of the second sub-trajectory based on a random selection of probe data points after a last junction probe data point (i.e. segmentation point) in the junction (see ¶0056, regarding segmentation unit 120 of apparatus 100 segments each route into at least two partial routes, where each partial route includes at least one waypoint as a segmentation point; ¶0054, regarding a segmentation point may be a waypoint that represents intersections and T-junctions; ¶0023-0024, regarding that waypoints in the region of the segmentation point are removed).
The “random selection of probe data points” may reasonably be taught by the waypoints that make up part of the region of the segmentation point that are removed (see ¶0023-0024).
Claims 6 and 19
Busser further discloses that the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
apply the gap placement after the junction in the sequence of location probe data points (see ¶0054, regarding that a segmentation point may be provided at locations such as a bus stop).
A bus stop is known to be at locations positioned away from junctions. The limitation of “after the junction” is not clearly defined as a particular location with respect to a junction.
Claim 7
As discussed in the rejection of claim 1, Yin teaches identifying the junction behavior (see ¶0031, with respect to Figures 1 and 4, regarding that road intersections are identified from the location data 20 obtained from a vehicle’s trajectory 21).
Yin further teaches determin[ing] one or more features based on latitude data associated with at least one vehicle (similar to the vehicle taught by Busser) during capture of one or more location probe data points within location data obtained from a vehicle’s trajectory 21, where the location data is defined as real world GPS data in ¶0028 (similar to the sequence of location probe data points taught by Busser) and longitude data associated with at least one vehicle (similar to the vehicle taught by Busser) during capture of one or more location probe data points within location data obtained from a vehicle’s trajectory 21, where the location data is defined as real world GPS data in ¶0028 (similar to the sequence of location probe data points taught by Busser) (see ¶0031, with respect to step 104 of Figure 2, regarding that node vectors are determined from the location data 20 obtained from at least one vehicle’s trajectory 21, where node vectors are determined for each target location (i.e. geographical coordinate from the location data), as described in ¶0035, and the geographical data is defined as coordinates that include latitudes and longitudes, as described in ¶0051), and identify[ing] the junction behavior based on the one or more features (see ¶0032-0034, with respect to step 106 of Figure 2, regarding that the node vectors are input into a trained multiscale classifier for determining whether the target location is a candidate location for a road intersection, where the identification of road intersections is performed for each target location, as described in ¶0035, and the plurality of candidate locations are clustered for the determination of a road intersection, as described in ¶0037 and ¶0057).
Claim 8
Yin further teaches apply[ing] the one or more data features (i.e. node vectors) to a machine learning model (i.e. trained multiscale classifier) configured to classify candidate locations of the location data obtained from a vehicle’s trajectory 21, where the location data is defined as real world GPS data in ¶0028 (similar to a portion of the sequence of location probe data points taught by Busser) as the junction behavior (see ¶0032-0034, with respect to step 106 of Figure 2, regarding that the node vectors are input to a trained multiscale classifier including a graph convolutional network 700 to provide a probability of the target location 14 being a road intersection, which is compared with a predetermined threshold for classifying the target location as a candidate location for a road intersection).
Claim 9
Yin further teaches training the machine learning model based on a set of labels associated with junction probe data points and non-junction probe data points (see ¶0046-0047, regarding that the classifier is trained using training data that includes location data obtained from at least one vehicle’s trajectory 21 and intersection presence data for each target location, e.g., ‘1’ when a road intersection is present and ‘0’ when a road intersection is not present).
Claim 10
Yin further teaches apply[ing] the one or more data features (i.e. node vectors) to a deterministic model (i.e. trained multiscale classifier) configured to classify candidate locations of the location data obtained from a vehicle’s trajectory 21, where the location data is defined as real world GPS data in ¶0028 (similar to a portion of the sequence of location probe data points taught by Busser) as the junction behavior (see ¶0032-0034, with respect to step 106 of Figure 2, regarding that the node vectors are input to a trained multiscale classifier including a graph convolutional network 700 to provide a probability of the target location 14 being a road intersection, which is compared with a predetermined threshold for classifying the target location as a candidate location for a road intersection). The trained multiscale classifier of Yin may reasonably teach a deterministic model, given the predictions generated by the final trained model are deterministic.
Claim 11
Yin further teaches configur[ing] the deterministic model based on a set of rules associated with junction probe data points and non-junction probe data points (see ¶0033, regarding that the multiscale classifier includes logistic regression, in which the probability is compared with a predetermined threshold to identify a road intersection, e.g., linear regression returns a ‘1’ when a road intersection is present and ‘0’ when a road intersection is not present, where the method is repeated for each target location, as described in ¶0035, with respect to Figure 2).
Claim 12
Busser further discloses that the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
identify a first portion in the sequence of location probe data points as a potential origin location of the vehicle during a journey associated with the travel of the vehicle along the portion of the road network (see ¶0012, regarding the recorded route includes a starting point to a destination point via successive waypoints, where the route is segmented by removing waypoints in a region of a segmentation point, as described in ¶0023);
apply the gap placement in the first portion in the sequence of location probe data points (see ¶0023, regarding that waypoints in the region of the segmentation point are removed, where the segmentation point may be an intersection or T-junction).
The partial route (i.e. “first portion”) that includes the starting point (e.g., partial route R2.1 includes starting point S2 in Figure 3) may reasonably teach a “potential origin location.” The term “potential origin location” is not defined in the Applicant’s specification and may reasonably pertain to the origin of a partial route, in light of paragraph [0098] of the specification filed 11/28/2022. The term “potential” does not require the “first portion” to be an origin location.
Yin further teaches identify[ing] the junction behavior in candidate locations of the location data obtained from a vehicle’s trajectory 21 (similar to the first portion of the sequence of location probe data points taught by Busser) based on one or more features (i.e. node vectors) for the location data (target data) obtained from a vehicle’s trajectory 21 (similar to the sequence of location probe data points taught by Busser) (see ¶0032-0034, with respect to step 106 of Figure 2, regarding that the node vectors are input into a trained multiscale classifier for determining whether the target location is a candidate locations for a road intersection, where the identification of road intersections is performed for each target location, as described in ¶0035, and the plurality of candidate locations are clustered for the determination of a road intersection, as described in ¶0037 and ¶0057). The claimed “gap placement” is not based on the identified junction behavior, and therefore, Yin may be reasonably applied to teach the claimed “identify” step.
Claim 13
Busser further discloses the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
identify a last portion in the sequence of location probe data points as a potential destination location of the vehicle during a journey associated with the travel of the vehicle along the portion of the road network (see ¶0012, regarding the recorded route includes a starting point to a destination point via successive waypoints, where the route is segmented by removing waypoints in a region of a segmentation point, as described in ¶0023);
apply the gap placement in the last portion in the sequence of location probe data points (see ¶0023, regarding that waypoints in the region of the segmentation point are removed, where the segmentation point may be an intersection, T-junction, highway exit, or bus stop).
The partial route (i.e. “last portion”) that includes the destination point (e.g., partial route R2.3 includes destination point Z2 in Figure 3) may reasonably teach a “potential destination location.” The term “potential destination location” is not defined in the Applicant’s specification and may reasonably pertain to the destination of a partial route, in light of paragraph [0093] of the specification filed 11/28/2022. The term “potential” does not require the “last portion” to be a destination location.
Yin further teaches identify[ing] the junction behavior in candidate locations of the location data obtained from a vehicle’s trajectory 21 (similar to the last portion of the sequence of location probe data points taught by Busser) based on one or more features (i.e. node vectors) for the location data (target data) obtained from a vehicle’s trajectory 21 (similar to the sequence of location probe data points taught by Busser) (see ¶0032-0034, with respect to step 106 of Figure 2, regarding that the node vectors are input into a trained multiscale classifier for determining whether the target location is a candidate locations for a road intersection, where the identification of road intersections is performed for each target location, as described in ¶0035, and the plurality of candidate locations are clustered for the determination of a road intersection, as described in ¶0037 and ¶0057). The claimed “gap placement” is not based on the identified junction behavior, and therefore, Yin may be reasonably applied to teach the claimed “identify” step.
Claim 14
The combination of Busser, Yin, Dorum, and Marumoto discloses the claimed computer-implemented method, as discussed in the rejection of claim 1.
Claim 20
The combination of Busser, Yin, Dorum, and Marumoto discloses the claimed computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein (see ¶0040 of Busser, regarding the invention is a computer program product loaded into a microprocessor and comprises code for carrying out the steps of the method), the computer-executable program code instructions comprising program code instructions to perform the steps described in the rejection of claim 1.
Busser further discloses that the claimed program code instructions are configured to cause transmission of the vehicle data to a server computing device (see ¶0028, regarding that the partial route data is output for evaluation or control, defined as being useful for providing innovative services, such as traffic jam reports in ¶0005). In case the limitation of “a server computing device” cannot be reasonably gleaned from Busser, with respect to the suggested innovative services in ¶0005 that apply to the partial route data that is output for evaluation purposes in ¶0028, Marumoto is applied in combination with Busser to teach the output of similar data to a server computing device.
Specifically, Marumoto teaches server 6 (similar to apparatus 100 in Figure 6 of Busser) receives recorded driving condition data (see ¶0055), defined as including vehicle positional data (latitude, longitude, and altitude) of a traveling route, as described in ¶0038. Marumoto further teaches that server 6 provides the driving condition data to a server computing device (see ¶0085, regarding server 6 provides driving condition data to traffic center server 8).
In Busser, as modified by Dorum, an apparatus records partial routes comprised of a sequence of locations augmented with elevation data. In Marumoto, an apparatus records a sequence of locations and associated altitude data. However, it is the transmission of recorded data representative of a route traveled by a vehicle to a server computing device that is modified by Marumoto; therefore, any operations to augment or anonymize the stored data do not influence this combination.
Since the systems of Busser and Marumoto are directed to the same purpose, i.e. receiving recorded vehicle data representative of a traveled route, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the step of cause transmission of the vehicle data of Busser to be to a server computing device, in the same manner that driving condition data is transmitted from a server of Marumoto to a traffic center server, with the predictable result of enhancing information concerning traffic accidents and sharing performance imposed on a server among a plurality of servers (¶0085 of Marumoto).
Claims 5 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Busser in view of Yin, Dorum, and Marumoto, and in further view of Biswas et al. (US 2018/0087913 A1), hereinafter Biswas.
Claims 5 and 18
Busser discloses the “first location probe data point” associated with a partial route with respect to a particular T-junction, e.g., segmentation point T1 in Figure 3, and does not further disclose that the computer program code instructions are configured to, when executed by the processing circuity, cause the apparatus to:
determine the first location probe data point of the second sub-trajectory based on a different junction associated with the sequence of location probe data points.
However, known alternative locations for segmentation points may be reasonably applied in light of ¶0054 of Busser, such that two junctions exist in proximity to one another where a different junction associated with the sequence of location points may reasonably determine a similar “first location probe data point,” in light of Biswas.
Specifically, Biswas teaches a similar system in which locations (similar to the sequence of location probe data points taught by Busser) are logged by mobile devices 2, 3 associated with a single vehicle 412 while traveling through two consecutive sub-portions 1-2, 2-3 (see ¶0107, with respect to Figures 8a and 8b). Similar to Busser, Biswas teaches removing the location data from point 12’ to point 23’, associated with an intersection, as depicted in Figure 7b (see ¶0108), such that point 23 (similar to the first location probe data point taught by Busser) of sub-portion 23-3 (similar to the second sub-trajectory taught by Busser) is determined based on a different junction associated with the logged locations (see Figure 7b, depicting the point 23 as positioned at intersection 723, while the removed location data starts at intersection 722).
In Busser, the sequence of location probe data points is recorded by a navigation system of a vehicle. In Biswas, the sequence of location probe data points is recorded by two mobile devices located inside of a vehicle. However, it is the configuration of the junction, such that first location probe data point of the second sub-trajectory is based on a different junction, that is modified by Biswas; therefore, the particular source of the sequence of location data points does not influence this combination.
Since the systems of Busser and Biswas are directed to the same purpose, i.e. recording a sequence of location points as a vehicle travels a route, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the junction configurations of Busser, so as to determine the first location probe data point of the second sub-trajectory based on a different junction associated with the sequence of location probe data points, in the same manner that Biswas teaches a configuration in which a second intersection defines the end of the gap of removed data, with the predictable result of creating more ambiguity by the plurality of incoming/outgoing roads and thus, increasing the degree of uncertainty in the location data (¶0102 of Biswas).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Specifically, Zuberi et al. (“Detection of Road Intersections Using History Trajectory Data for Evolving Mix-Zones,” 2014, Department of Electronics & Communications, Jamia Millia Islamia, New Delhi-11025) teaches the use of mix-zones at intersections to protect location privacy of mobile users, and Mao et al. (US 2019/0360819 A1) teaches removing probe data points within an intersection for map matching probe data points to road segments (see ¶0061).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SARA J LEWANDROSKI/Examiner, Art Unit 3661
/RAMYA P BURGESS/Supervisory Patent Examiner, Art Unit 3661