DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This final action is in response to Applicant’s filing dated December 15, 2025. Claims 1-6 are currently pending and have been considered, as provided in more detail below. Claims 1 and 6 have been amended.
*Examiner Note: Claim language is bolded. Cited References and Applicant’s arguments are italicized. Examiner interpretations are preceded with an asterisk *.
Response to Arguments
Applicant’s arguments filed 12/15/25 have been considered but are moot because the arguments are directed toward subject matter that has not been previously considered and has necessitated a new ground of rejection as outlined below. While the new ground of rejection may rely on some of the previous references applied in the prior rejection of record, new additional references have been added to the combination and introduced for Applicant’s consideration given the amended independent claims as discussed in detail below.
Response to Amendment
Regarding the rejections under 35 USC §101, amendments made to the claims fail to overcome the rejections. The rejections under 35 USC §101 are maintained as outlined below.
Regarding the rejections under 35 USC §103, the amendments made to the claims have necessitated new grounds of rejections as outlined 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 1-6 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Regarding Step 1 of the Revised Guidance, it must be considered whether the claims are directed to one of the four statutory classes of invention. In the instant case, claim 1 is directed to a an information provider (i.e., a machine) and claim 6 is directed to an information providing method (i.e., a process) and recites at least one step. Therefore, claims 1 and 6 are within at least one of the four statutory categories (processes, machines, manufactures and compositions of matter.
101 Analysis – Step 2A, Prong 1
Regarding Prong 1 of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite a judicial exception (subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) mental processes, and/or c) certain methods of organizing human activity).
Independent claim 6 includes limitations that recite an abstract idea (bolded below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 6 recites:
An information providing method that is performed by a computer, the method
comprising:
a receiving step comprising:
receiving, via a communication unit, consecutive position information at predetermined time intervals from each of a plurality of mobile objects, along with a mobile object ID and time information, during a period from a start time to a stop time of the mobile object; and
accumulating the received position information and time information as data keyed by the mobile object ID in a position information database; a storing step of storing map information that includes a road map; a departure/arrival point position information generating step comprising:
based on a position information database in which time-discretely varying position information for each of a plurality of mobile objects is accumulated, calculating, for each of the mobile objects during a predetermined period, a highest frequency value associated with departure/arrival point position information, wherein the departure/arrival point position is defined as a position where the mobile object parked during travel and subsequently departed after parking;
estimating that the position corresponding to the highest frequency values represents a location near the residence of the user of the mobile object and
generating, as departure/arrival point position information for the mobile object, surface information including a position corresponding to the highest frequency value, in place of the highest frequency position information, the surface information being configured so that the location near the residence of the user cannot be estimated; and
a position information outputting step comprising:
for each of a plurality of mobile objects, outputting a travel route from a departure point position to an arrival point position;
determining whether the departure point position or the arrival point position corresponds to a most frequent departure or arrival location of the mobile object;
in response to the determination, replacing the corresponding departure and/or arrival point position information with surface information representing the most frequent departure or arrival location;
outputting the surface information including a position corresponding to a highest frequency value;
outputting position information of a position that is separated by a predetermined distance or greater from the position having the highest frequency value, and of subsequent positions following said position; and
enabling analysis including a movement route and stay positions of the mobile object, while ensuring protection of position information associated with personal data of a user of the mobile object.
The Examiner submits that the foregoing bolded limitations constitute a judicial exception in terms of a “mental process” because under its broadest reasonable interpretation, the claim limitations can be “performed in the human mind such as observation, evaluation, judgement and inference, as well as mathematical concepts including statistical analysis (i.e., determining a highest frequency value), and the collection and analysis of information. See MPEP 2106.04(a)(2)(II) and MPEP 2106.04(a)(2)(III).
The independent claim 6 recites the limitations of a receiving step comprising: receiving consecutive position information at predetermined time intervals from each of a plurality of mobile objects, along with a mobile object ID and time information, during a period from a start time to a stop time; and accumulating the received position information and time information as data keyed; a storing step of storing map information that includes a road map; in which time-discretely varying position information for each of a plurality of mobile objects is accumulated, calculating, for each of the mobile objects during a predetermined period, a highest frequency value associated with departure/arrival point position information, wherein the departure/arrival point position is defined as a position where the mobile object parked during travel and subsequently departed after parking; estimating that the position corresponding to the highest frequency values represents a location near the residence of the user of the mobile object and generating, as departure/arrival point position information for the mobile object, surface information including a position corresponding to the highest frequency value, in place of the highest frequency position information, outputting a travel route from a departure point position to an arrival point position; determining whether the departure point position or the arrival point position corresponds to a most frequent departure or arrival location of the mobile object; in response to the determination, replacing the corresponding departure and/or arrival point position information with surface information representing the most frequent departure or arrival location; outputting the surface information including a position corresponding to a highest frequency value; outputting position information of a position that is separated by a predetermined distance or greater from the position having the highest frequency value, and of subsequent positions following said position; and enabling analysis including a movement route and stay positions of the mobile object, while ensuring protection of position information associated with personal data of a user of the mobile object. These limitations, as drafted, are processes that, under their broadest reasonable interpretation, cover certain methods of organizing human activity and performance of the limitation in the mind but for the recitation of “a communication unit”, “a position information database”, “a plurality of mobile objects” and “a road map”. There is nothing in the claim that precludes the steps from practically being performed in the mind. For example, this claim is directed to only an abstract idea on a generic computer and there is no clear technical improvement to the plurality of mobile objects or the road map.
The claim recites receiving and accumulating position information, calculating a highest frequency value, estimating a residence location, determining whether locations correspond to frequently occurring locations, and outputting processed information. Such limitations recite evaluating and analyzing data, which can be conceptually performed in the human mind or with pen and paper.
The mobile objects and the road map that is claimed, are additional elements, that are just general data gathering and rule implementation with an abstract idea of analyzing and outputting operations and there are no concrete technical elements present to improve the objects. The information provider is just collecting data and receiving the data and that is just a high level of generality at the applied level. There is no significance of the structure. There is no particular machine and the steps are mentioned at a high level of generality. The mere nominal recitation of a system does not take the claim limitations out of the certain methods of organizing human activity or the mental process grouping.
Additionally, the information providing system with a receiving step and a storing step, under the broadest reasonable interpretation, covers a process that is practically performed in the human mind.
Thus, the claim recites methods of organizing human activity and a mental process.
101 Analysis – Step 2A, Prong 2 evaluation: Practical Application - No
In Step 2A, Prong two of the 2019 PEG, a claim is to be evaluated whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in MPEP 2106.04(d), 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, such that the claim is more than a drafting effort designed to monopolize the judicial exception. The courts have indicated that additional elements such as: 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.”
The Office submits that the foregoing underlined limitation(s) recite additional elements that do not integrate the recited judicial exception into a practical application. In the instant application, the additional limitations beyond the above-noted abstract ideas are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”): In claim 6:
An information providing method that is performed by a computer, the method
comprising:
a receiving step comprising:
receiving, via a communication unit, consecutive position information at predetermined time intervals from each of a plurality of mobile objects, along with a mobile object ID and time information, during a period from a start time to a stop time of the mobile object; and
accumulating the received position information and time information as data keyed by the mobile object ID in a position information database; a storing step of storing map information that includes a road map; a departure/arrival point position information generating step comprising:
based on a position information database in which time-discretely varying position information for each of a plurality of mobile objects is accumulated, calculating, for each of the mobile objects during a predetermined period, a highest frequency value associated with departure/arrival point position information, wherein the departure/arrival point position is defined as a position where the mobile object parked during travel and subsequently departed after parking;
estimating that the position corresponding to the highest frequency values represents a location near the residence of the user of the mobile object and
generating, as departure/arrival point position information for the mobile object, surface information including a position corresponding to the highest frequency value, in place of the highest frequency position information, the surface information being configured so that the location near the residence of the user cannot be estimated; and
a position information outputting step comprising:
for each of a plurality of mobile objects, outputting a travel route from a departure point position to an arrival point position;
determining whether the departure point position or the arrival point position corresponds to a most frequent departure or arrival location of the mobile object;
in response to the determination, replacing the corresponding departure and/or arrival point position information with surface information representing the most frequent departure or arrival location;
outputting the surface information including a position corresponding to a highest frequency value;
outputting position information of a position that is separated by a predetermined distance or greater from the position having the highest frequency value, and of subsequent positions following said position; and
enabling analysis including a movement route and stay positions of the mobile object, while ensuring protection of position information associated with personal data of a user of the mobile object.
The claim recites the additional elements of “a communication unit”; “a position information database”; “a plurality of objects” and “a road map” The elements of a receiving step of receiving position information and a storing step of storing map information are such that one can mentally receive position information and store map information. There is no particular machine and only a generic system mentioned at a high level of generality. There is no structure for improving the system and there is only a collection and output of data and a mental judgement made for using the data of the mobile objects.
Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B evaluation: Inventive Concept: - No
In Step 2B of the 2019 PEG, the claim(s) is to be evaluated as to 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. See MPEP 2106.05.
Thus, the claim 6 is ineligible. Independent claim 1 is also ineligible under the same rational as provided for in the rejection of independent claim 6.
101 Analysis – Dependent Claims
Dependent claims 2-5 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 [these dependent claims inherit the abstract idea set forth in claim 1. No other technology or action has been recited in claims 2-5 to integrate the abstract idea into a practical application nor to amount to significantly more than the abstract idea. Thus, claims 2-5 also do not confer eligibility on the claimed invention and are ineligible for reasons stated above and for similar reasons to claim 6]. Therefore, dependent claims 2-5 are not patent eligible under the same rationale as provided for in the rejection of independent claims 1 and 6.
Therefore, claims 1-5 are also ineligible under 35 USC §101.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1 and 6 recite the limitation "the residence of the user" in line 23. There is insufficient antecedent basis for this limitation in these claims. These claims have antecedent basis issues (see MPEP 2173.05(e)). Generally, the first time a claim element is introduced “a” or “an” (as grammatically appropriate) should be used. When subsequently referring back to a claim element already introduced “the” or “said” is used to make it clear which element precisely is being referred to.
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 and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Hosokawa (US 2020/0184820A1) in view of Kondo (US 2021/0348936A1) in view of Herlocker (US 2018/0268168A1).
Regarding amended claim 1, Hosokawa discloses An information provider (see at least para.
[0035] of Hosokawa which discloses “the subsystem 200 may provide notification about the event information” and see at least para. [0049] of Hosokawa which discloses “the receiving section 150 may receive car probe data from each mobile object 10 as the information. The car probe data may include information detected by the mobile object 10, such as position information of the mobile object 10”, *These disclosures correspond to a system that collects probe data from mobile objects and provides information based on that probe data, which reasonably corresponds to the claimed information provider) comprising: a receiver (Fig. 3, 150 and see at least para. [0040] of Hosokawa which discloses ”a receiving section 150”) configured to: receive, via a communication unit (see at least para. [0051] of Hosokawa which discloses “The receiving section 150 may communicate with the plurality of mobile objects 10 and receive the car probe data of each mobile object 10, via the Internet 40. The receiving section 150 may receive the car probe data of the plurality of mobile objects 10 through wireless communication, a subscriber network, a cellular network, or any desired combination of network”, *Communication through such networks corresponds to the claimed communication unit through which the receiver obtains the transmitted information), consecutive position information (see at least para. [0047] of Hosokawa which discloses “the position information of the mobile object 10” and see at least para. [0049] of Hosokawa which discloses “The receiving section 150 may be operable to receive information transmitted from each of a plurality of mobile objects 10. Each mobile object 10 may transmit information at designated time intervals, and the receiving section 150 may sequentially receive this transmitted information”, *Transmission of position information at designated time intervals and sequential reception of the transmitted probe data corresponds to receiving consecutive position information at predetermined time intervals as broadly as recited) at predetermined time intervals (see at least para. [0049] of Hosokawa which discloses “Each mobile object 10 may transmit information at designated time intervals”) from each of a plurality of mobile objects along with a mobile object ID (see at least para. [0083] of Hosokawa which discloses “the ID of the mobile object based on the calculation using the ID. Then, the mobile object server may provide the object server managing the identified object agent with the setting data including the position information, the ID of the mobile object, and ID(s) of passenger(s) of the mobile object via the gateway apparatus”) and time information, and accumulate the received position information and time information as data keyed by the mobile object ID (see at least para. [0048] of Hosokawa which discloses “The determining section 146 may store the position information of this mobile object 10 and/or information of the determined region in the storage section 142, in association with this mobile object 10. The determining section 146 may store a history of the position information of this mobile object 10 and/or a history of the determined mobile object server 220 in the storage section 142”, *Storing a history of the position information corresponds to accumulating the received position information over time and Hosokawa further discloses that the stored information is associated with the mobile object, which corresponds to storing the accumulated position information as data keyed by the mobile ID) in a position information database (see at least para. [0127] of Hosokawa which discloses “The mobile object database 2300 may store the reliability with which each of a plurality of mobile objects 10 moving in a geographic space detects an event (referred to as the detection reliability). For example, the mobile object database 2300 may store the detection reliability of each mobile object 10 in association with each of the plurality of mobile objects 10. Furthermore, the mobile object database 2300 may store the detection reliability of each mobile object 10 in association with each of the one or more sensors 11 of the mobile object 10”, *Since Hosokawa also discloses a mobile object database that stores information associated with each mobile object, this corresponds to the claimed position information database under the broadest reasonable interpretation); a storage (Fig. 3, 142 and see at least para. [0045] of Hosokawa which discloses “The storage section 142 may be operable to communicate with the dividing section 130 and store information concerning the plurality of first regions and the plurality of second regions”, *Examiner interprets the information on the regions to be map information) configured to store map information (see at least para. [0138] of Hosokawa which discloses “map information of the geographic space possessed by the one mobile object 10”) including a road map (see at least para. [0041] of Hosokawa which discloses “The acquiring section 110 may be operable to acquire map data corresponding to the geographical areas where a mobile object 10 is positioned, from an external database 30, for example. In response to the map being updated, the acquiring section 110 may acquire some or all of the updated map data. The acquiring section 110 may be operable to acquire the map data from the Internet, a subscriber network, a cellular network, or any desired combination of networks. The system 100 may be operable to store the map data”, *Examiner interprets the map data of the geographical areas to be a road map).
Hosokawa does disclose based on a position information database (see at least para.
[0128] of Hosokawa which discloses “The mobile object database 2300 may store statistical information of detection results of events/candidate events by the plurality of mobile objects 10”) in which position information varying (see at least para. [0047] of Hosokawa which discloses “The determining section 146 may be operable to communicate with the storage section 142, and determine one region from the plurality of regions (e.g., regions A-F of FIG. 1) in which each of the mobile objects 10 is located based on the position information of the mobile object 10 and geographic information of the plurality of regions. The determining section 146 may identify a route or position in the map area managed by the system 100 that corresponds to the position information of the mobile object 10” ) over discrete time intervals (see at least para. [0049] of Hosokawa which discloses “Each mobile object 10 may transmit information at designated time intervals, and the receiving section 150 may sequentially receive this transmitted information” and see at least para. [0036] of Hosokawa which discloses “the region corresponding to the position of the mobile object 10 might change” and see at least para. [0131] of Hosokawa which discloses “The dynamic map may be a high-definition digital geographic map that incorporates not only information concerning geographic objects, but also event information that changes over time, such as accidents, traffic jams, and construction regulations”, *Examiner interprets this as the position information changing over time, *This corresponds to accumulating position information over time per mobile object in a database (car probe data, histories per object), so it supports the “position information … varying over discrete time intervals .. accumulate” aspect (see at least para. [0036] of Hosokawa which discloses “the region corresponding to the position of the mobile object 10 might change” and see at least para. [0131] of Hosokawa which discloses “The dynamic map may be a high-definition digital geographic map that incorporates not only information concerning geographic objects, but also event information that changes over time, such as accidents, traffic jams, and construction regulations”, *Examiner interprets this as the position information changing over time); for each of the mobile objects during a predetermined period (see at least para. [0049] of Hosokawa which discloses “The receiving section 150 may be operable to receive information transmitted from each of a plurality of mobile objects 10. Each mobile object 10 may transmit information at designated time intervals, and the receiving section 150 may sequentially receive this transmitted information. In this embodiment, the receiving section 150 may receive car probe data from each mobile object 10 as the information. The car probe data may include information detected by the mobile object 10, such as position information of the mobile object 10”), for each of the plurality of mobile objects is accumulated (see at least para. [0048] of Hosokawa which discloses “The determining section 146 may store a history of the position information of this mobile object 10 and/or a history of the determined mobile object server 220 in the storage section 142” and see at least para. [0137] of Hosokawa which discloses “the mobile object server 220 may calculate the MPP of one mobile object 10. For example, the mobile object server 220 may calculate the MPP using, in addition to the current travel history of the one mobile object 10, at least one of pattern matching that utilizes the travel history up to the most recent travel history for the one mobile object 10, the travel state of another mobile object 10 at the current time point, and the current time range, day of the week, and the like”).
Hosokawa may not explicitly disclose during a period from a start time to a stop time of the
mobile object.
However, Hosokawa does teach continuous probe acquisition because Hosokawa already
acquires sequences of probe data over time at designated intervals while the mobile object moves, and stores them per mobile object (see at least para. [0152] of Hosokawa which discloses “a case in which detection results from a plurality of mobile objects 10 are received continuously in a short time for an unknown event/candidate event”. Hosokawa further discloses that each mobile object transmits information at designated time intervals while the mobile object is traveling, and the receiving section sequentially receives this transmitted information, thereby accumulating time-series probe data per mobile object.
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention, in view of Hosokawa’s continuous acquisition of per vehicle probe data, to treat the period between a vehicle start (i.e., ignition on/departure) and a vehicle stop (engine off/parking) as a “trip” and to regard the probe data collected during that trip as being received during a period from a start time to a stop time of the mobile object, since such start/stop based trip segmentation is a routine and widely used practice in vehicle telematics.
Hosokawa may not explicitly disclose a departure/arrival point position information
generator configured to: calculate, for each of the mobile objects during a predetermined period, a highest frequency value associated with departure/arrival point position information, wherein the departure/arrival point position is defined as a position where the mobile object parked during travel and subsequently departed after parking; and generate, as departure/arrival point position information for the mobile object, surface information including a position corresponding to the highest frequency value; a position information outputter configured to: output, for each of the plurality of mobile objects, a travel route from a departure point position to an arrival point position; determine whether the departure point position or the arrival point position corresponds to a most frequent departure or arrival location of the mobile object; output the surface information including a position corresponding to a highest frequency value.
However, Kondo discloses a departure/arrival point position information generator (see at
least para. [0036] of Kondo which discloses “the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination” and see at least para. [0073] of Kondo which discloses “the destination estimation unit 209 sets the point ID designated by the arrival place determination processing unit 206 (point ID transferred from the arrival place determination processing unit 206) as the departure point ID (S301), and then acquires the most frequent destination point ID among the departure point IDs from the departure place/destination table 210 (S302). In other words, in step S302, the destination estimation unit 209 selects the destination point ID in which the information of the number of times 403 is most frequent among the departure point IDs set in step S301 from the departure place/destination table 210” and see at least para. [0085] of Kondo which discloses “the route estimation unit 212 estimates the most frequent route from the designated “departure link” to the arrival link”) configured to: calculate (see at least para. [0074] of Kondo which discloses “calculating the most frequent destination point), a highest frequency value (see at least para. [0073] of Kondo which discloses “Thus, when calculating the most frequent destination point ID the number of times of the same destination point ID is totaled, and the departure point ID of the most frequent number of times is selected”) associated with departure/arrival point position information (see at least para. [0085] of Kondo which discloses “the route estimation unit 212 estimates the most frequent route from the designated “departure link” to the arrival link, sets the route that was estimated as the estimated route (S404), and thereafter ends the processing of this routine. In other words, in step S404, the most frequent route from the set departure link to the arrival link is estimated, and the route that was estimated is set as the estimated route. When estimating the most frequent route, foremost, the departure link is designated as the entry link, and the ID of the exit link 502 in which the information of the number of times 503 is most frequent is acquired. Furthermore, with such exit link as the departure link, the ID of the exit link in which the information of the number of times 503 is most frequent is acquired, and this process is repeated from the “departure link” to the arrival link to trace the exit link in which the information of the number of times 503 is most frequent in order to estimate the most frequent route”), wherein the departure/arrival point position is defined as a position where the mobile object parked during travel and subsequently departed after parking (*Kondo discloses that route and frequency information are associated with departure and arrival links, which correspond to departure/arrival point position information. In particular, para. [0085] of Kondo describes a route estimation unit 212 that “estimates the most frequent route from the designated “departure link” to the arrival link” and when estimating the most frequent route, repeatedly selects from a table, the exit link whose number of time value is most frequent from the departure link to the arrival link. Therefore, Kondo teaches route and frequency information associated with departure and arrival positions on the map. Additionally, Kondo stores parking information as a history of the vehicle having parked in an area near a destination, and uses these parking positions are arrival (and departure) points, corresponding to positions where the vehicle parked during travel and subsequently departed after parking); and generate, as departure/arrival point position information for the mobile object (see at least para. [0036] of Kondo which discloses “the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination” and see at least para. [0073] of Kondo which discloses “the destination estimation unit 209 sets the point ID designated by the arrival place determination processing unit 206 (point ID transferred from the arrival place determination processing unit 206) as the departure point ID (S301), and then acquires the most frequent destination point ID among the departure point IDs from the departure place/destination table 210 (S302). In other words, in step S302, the destination estimation unit 209 selects the destination point ID in which the information of the number of times 403 is most frequent among the departure point IDs set in step S301 from the departure place/destination table 210” and see at least para. [0085] of Kondo which discloses “the route estimation unit 212 estimates the most frequent route from the designated “departure link” to the arrival link”), surface information (see at least para. [0036] of Kondo which discloses “the information of the point from the point information table 207, refers to the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination“) including a position corresponding to the highest frequency value (see at least para. [0073] of Kondo which discloses “Thus, when calculating the most frequent destination point ID the number of times of the same destination point ID is totaled, and the departure point ID of the most frequent number of times is selected”); a position information outputter (see at least para. [0108] of Kondo which discloses “output guidance information as information which guides the vehicle based on the recommendation information 215 and which includes at least a parking position in the parking lot. The recommendation unit 214 can thereby guide the vehicle (driver) to the parking position based on the guidance information when the vehicle arrives at the facility”, *Examiner interprets this output of guidance information to be the position information outputter) configured to: output, for each of the plurality of mobile objects, a travel route (see at least para. [0039] of Kondo which discloses “The route estimation unit 212 estimates the route to the destination estimated by the destination estimation unit 209. Here, the route estimation unit 212 estimates the route to the destination by using the travel history 213”) from a departure point position to an arrival point position (Kondo discloses outputting a travel route from a departure point position to an arrival point position. In particular, a route estimation unit 212 estimates the most frequent route from the designated departure link to the arrival link based on frequency information in a table and sets that route as the estimated route for output. The departure link corresponds to the departure point position (parking area entrance/departure place), and the arrival link corresponds to the arrival point position (destination parking area), thereby teaching output of a travel route from a departure point position to an arrival point position for the vehicle/mobile object); determine whether the departure point position or the arrival point position (see at least para. [0033] of Kondo which discloses “whether the vehicle has arrived at the entrance of the facility including the parking lot in the vicinity of the destination of the vehicle based on the positron information (position information based on the positioning of the positioning sensor 103) indicating the position of the vehicle on the map”) corresponds to a most frequent departure or arrival location of the mobile object (see at least para. [0070] of Kondo which discloses “The point ID of the departure point ID 401 and the point ID of the destination point ID 402 store information (for example, “1” to “5”) existing in the point ID 301 of the point information table 207. When referring to the information of each point ID, information of the corresponding point ID is acquired from the point information table 207”, *Kondo discloses determining whether the departure point position or arrival point position corresponds to a most frequent departure or arrival location. When a vehicle arrives at a parking area entrance (departure point ID), the destination estimation unit 209 sets that point as the departure point ID and then “acquires the most frequent destination point ID amount the departure point IDs from the departure place/destination table 210” by selecting the destination with the highest “number of times” value. This determines whether the current arrival destination corresponds to a most frequent arrival location for the vehicle based on its historical departure/destination table. The route estimation unit then confirms by estimating the most frequent route from the departure to that arrival point); output the surface information (see at least para. [0036] of Kondo which discloses “the information of the point from the point information table 207, refers to the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination“) including a position corresponding to a highest frequency value (see at least para. [0073] of Kondo which discloses “Thus, when calculating the most frequent destination point ID the number of times of the same destination point ID is totaled, and the departure point ID of the most frequent number of times is selected”).
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the system of Hosokawa to include a departure/arrival point position information generator configured to: calculate, for each of the mobile objects during a predetermined period, a highest frequency value associated with departure/arrival point position information, wherein the departure/arrival point position is defined as a position where the mobile object parked during travel and subsequently departed after parking; and generate, as departure/arrival point position information for the mobile object, surface information including a position corresponding to the highest frequency value; a position information outputter configured to: output, for each of the plurality of mobile objects, a travel route from a departure point position to an arrival point position; determine whether the departure point position or the arrival point position corresponds to a most frequent departure or arrival location of the mobile object; output the surface information including a position corresponding to a highest frequency value; as taught in Kondo with a reasonable expectation of success in order to leverage established travel history analysis for accurate original/destination prediction in statistical mobility systems. This modification provides the predictable benefit of higher accuracy in statistical route outputs while Hosokawa’s surface generation ensures individual privacy protection, addressing both data utility and privacy concerns in mobility datasets.
Hosokawa, as modified by Kondo does disclose determining most frequent destinations
based on frequency values. In particular, see at least para. [0073] of Kondo which discloses “Thus, when calculating the most frequent destination point ID the number of times of the same destination point ID is totaled, and the departure point ID of the most frequent number of times is selected”, *This corresponds to using a highest frequency value (most frequent number of times) for departure/destination combinations).
Hosokawa in view of Kondo may not explicitly disclose estimate that the position
corresponding to the highest frequency value represents a location near the residence of the user of the mobile object.
However, Herlocker (US2018/0268168) discloses estimate that the position corresponding
to the highest frequency value represents a location near the residence of the user of the mobile object (see at least para. [0015] of Herlocker which discloses “a user's trip from home to work can be represented in telemetry data by a single trace. In this example, the first point of the associated trace is associated with the location of the user's home and the last point of the trace associated with the user's work. The path taken from the user's home to the user's work can be represented in a series of intermediate points between the first and last points of the trace and one or more links between adjacent points of the trace. As each trace represents a single trip, many traces for a single device may be collected in a single day and many more over a longer period. For example, over a period of a month, twenty traces may be collected for a user's trips from home to work. Because telemetry data often includes a time stamp, a trace will also in many cases be indicative of what time the user of the device left home and when the user arrived at work”).
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the claimed information provider of Hosokawa, as modified by Kondo, to estimate that the position corresponding to the highest frequency value represents a location near the residence of the user of the mobile object, as taught in Herlocker with a reasonable expectation of success in order to facilitate the output of only surface information, i.e., an obfuscated area and position information of points at least a predetermined distance away from that position, in order to protect the user’s personal data by preventing third parties from inferring the precise location of the user’s home or other sensitive endpoints from shared trajectory data, while still enabling analysis of routes and stay positions as taught in Herlocker’s anonymization of geographic route trace endpoints. See para. [0016]-[0017] for motivation.
Hosokawa, as modified by Kondo may also not explicitly disclose and in place of the highest
frequency position information, the surface information being configured so that the location near the residence of the user cannot be estimated; in response to the determination, replace the corresponding departure and/or arrival point position information with surface information representing the most frequent departure or arrival location; output position information of a position separated by a predetermined distance or greater from the position having the highest frequency value, and of subsequent positions following said position and enable analysis including a movement route and stay positions of the mobile object, while ensuring protection of position information associated with personal data of a user of the mobile object.
However, Herlocker discloses and in place of the highest frequency position information,
the surface information being configured so that the location near the residence of the user cannot be estimated (see at least para. [0047] of Herlocker which discloses “the client device associated with the first trace 202 could be associated with a user living at the address associated with the first origin point 206 based at least in part on the first trace 202. Therefore, in some embodimnts, certain sections of received traces may be removed to obfuscate the original origin 206 and destination 208 points of a trace or other relevant sections of the trace … The first cutoff 214 divides the first origin section 218 containing the first origin point 206 from the remainder of the trace 202. That is, the first origin cutoff 214 divides the points of telemetry data associated with the first trace 202 into two sections, the first origin section 218 and a section comprising the remaining points associated with the trace. In the embodiment of FIG. 2A, the first origin section 218 includes multiple points (including the first origin point 206) and connections between points. In some implementations, the section containing the origin point 206 (in this case the first origin section 218) is discarded, thereby obscuring the original origin point of the trace. In this way, it can be more difficult to determine personal user information such as a user's home using trace data including the first trace 206 or the second trace 204. This process can be repeated to generate a first destination cutoff, then determine and discard a destination section including the first destination point 208 to obscure the original destination of the first trace 202”, *Instead of outputting the exact origin/destination points, Herlocker discards the origin section (including origin point 206) and destination section (including destination point 208), thereby replacing the exact home/work position information with cropped traces from which “it can be more difficult to determine personal user information such as a user’s home” – see at least para. [0047] of Herlocker); in response to the determination, replace the corresponding departure and/or arrival point position information with surface information representing the most frequent departure or arrival location (see at least para. [0047] of Herlocker which discloses “the first origin section 218 includes multiple points (including the first origin point 206) and connections between points. In some implementations, the section containing the origin point 206 (in this case the first origin section 218) is discarded, thereby obscuring the original origin point of the trace. In this way, it can be more difficult to determine personal user information such as a user's home using trace data including the first trace 206 or the second trace 204. This process can be repeated to generate a first destination cutoff, then determine and discard a destination section including the first destination point 208 to obscure the original destination of the first trace 202”, *Herlocker teaches replacing departure arrival position information (origin/destination points) with information representing those locations in anonymized form. While Herlocker describes discarding the origin section (including origin point 206) and destination section (including destination point 208) from the original trace, the result is an anonymized trace that represents the same frequent departure/arrival locations (home/work endpoints) without revealing their exact positions. A person of ordinary skill in the art would understand that outputting the anonymized trace in place of the full trace with exact endpoints constitutes replacing the precises departure/arrival position information with a representation (the cropped trace) of those locations); output position information of a position separated by a predetermined distance or greater from the position having the highest frequency value, and of subsequent positions following said position (Herlocker teaches outputting position information of positions separated by a predetermined distance or greater from the highest-frequency endpoint positions (origin/destination = home/work), and subsequent positions following those endpoints. See at least para. [0046] of Herlocker which discloses “The first trace 202 comprises a first origin point 206 and a first destination point 208 connected by a plurality of intermediate points. The first origin point 206 and the first destination point 208 represent the starting and ending locations, respectively, for a trip associated with the trace”). Herlocker discards the origin section (multiple points including origin point 206) and destination section (multiple points including destination point 208) from the trace, based on sectioning criteria, and outputs only the intermediate anonymized trace (positions beyond the cutoff distance from endpoints, and subsequent positions along the route). The cutoff effectively defines a predetermined distance threshold from the origin/destination (highest-frequency positions), beyond which the subsequent route positions are output, as claimed); and enable analysis including a movement route and stay positions of the mobile object (see at least para. [0047] of Herlocker which discloses “trace data can be used to determine personal information about the associated user, for example the locations of the user's home, workplace, and other significant locations visited by the user”, *Examiner interprets this determination of personal data to correspond to movement route and stay position analysis. Such analysis of trace data necessarily involves analyzing the sequence of locations visited by the user and identifying locations where the user remains, which corresponds to analysis of movement routes and stay positions of the mobile object), while ensuring protection of position information associated with personal data of a user of the mobile object (see at least para. [0047] of Herlocker which discloses “the first origin section 218 includes multiple points (including the first origin point 206) and connections between points. In some implementations, the section containing the origin point 206 (in this case the first origin section 218) is discarded, thereby obscuring the original origin point of the trace. In this way, it can be more difficult to determine personal user information such as a user's home using trace data including the first trace 206 or the second trace 204. This process can be repeated to generate a first destination cutoff, then determine and discard a destination section including the first destination point 208 to obscure the original destination of the first trace 202”, *Examiner interprets that this anonymization process makes it more difficult to determine personal user information such as a user’s home using trace data, thereby ensuring protection of position information associated with personal data while enabling analysis of the preserved movement route data).
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to further modify the system of Hosokawa, as modified by Kondo, to include and in place of the highest frequency position information, the surface information being configured so that the location near the residence of the user cannot be estimated, in response to the determination, replace the corresponding departure and/or arrival point position information with surface information representing the most frequent departure or arrival location; output position information of a position separated by a predetermined distance or greater from the position having the highest frequency value, and of subsequent positions following said position and enable analysis including a movement route and stay positions of the mobile object, while ensuring protection of position information associated with personal data of a user of the mobile object; as taught in Herlocker with a reasonable expectation of success in order to protect user privacy by obfuscating the precise location of the user’s home or other sensitive endpoints in shared trajectory data, thereby preventing third parties from inferring personal information such as a user’s residence while still enabling the analysis and sharing of movement routes and stay positions for fleet management, navigation improvement, and traffic analytics and in order to enable analysis of vehicle movement patterns while reducing the risk of exposing sensitive user location information such as home or frequently visited locations. See para. [0047] of Herlocker for motivation.
Regarding claim 2, Hosokawa, as modified by Kondo and Herlocker discloses wherein the
surface information is a mesh of a predetermined area or greater (see at least para. [0030] of Hosokawa which discloses “The system 100 includes a plurality of subsystems 200 that respectively manage the plurality of regions. FIG. 1 shows an example in which the map area is divided into six regions from region A to region F, and six subsystems 200 respectively manage these six regions”, *Examiner interprets each region to be a predetermined area and the regions combined satisfy the “or greater” element of the claim because para. [0094] of Applicant’s specification describes “the mesh of a predetermined area or greater that includes the most frequent departure/arrival point position that is specified. In a case in which the mesh is generated as surface information, the mesh may include, for example, a predetermined number or greater of home positions of the vehicles 50” and it is clear that each region of Hosokawa can include the most frequent departure/arrival point positions).
Regarding claim 3, the combination of Hosokawa in view of Kondo and Herlocker discloses
the surface information (see at least para. [0079] of Hosokawa which discloses “Since each event server divides a number of events occurring on its managing regions into a plurality of areas by utilizing the event agents, it can efficiently handle event information”, *Examiner interprets the plurality of areas to have information and to be capable of including the administrative section since this can include the frequent departure/arrival point positions that can happen in the plurality of areas that are managed regions and see at least para. [0036] of Kondo which discloses “the information of the point from the point information table 207, refers to the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination“).
Kondo further discloses wherein the surface information is an administrative section (see
at least para. [0036] of Kondo which discloses “the information of the point from the point information table 207, refers to the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination”, *Examiner interprets the departure and destination places to be an administrative section because para. [0094] of Applicant’s specification describes “an administrative section that is predetermined and includes the most frequent departure/arrival point position”).
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to further modify the information provider of Hosokawa, as modified by Kondo and Herlocker, to include wherein the surface information is an administrative section, as further taught by Kondo with a reasonable expectation of success in order to facilitate more effective collection of position information.
Regarding claim 4, the combination of Hosokawa in view of Kondo and Herlocker discloses
wherein the position that is separated by the predetermined distance (see at least para. [0029] of Kondo which discloses “determination unit 202 determines whether the vehicle has stopped by setting a constant value to the vehicle speed or the travel distance of the vehicle, such as when the vehicle speed is near 0 for a fixed period of time or when there is hardly any movement in the position of the vehicle (there is hardly any travel distance of the vehicle) from the position information”, *Examiner interprets set value of the travel distance to be a predetermined distance) or greater from the position that has the highest frequency value (see at least para. [0073] of Kondo which discloses “the most frequent destination point ID among the departure point IDs from the departure place/destination table 210 (S302). In other words, in step S302, the destination estimation unit 209 selects the destination point ID in which the information of the number of times 403 is most frequent among the departure point IDs set in step S301 from the departure place/destination”, *Examiner interprets the most frequent point, to be the position with the highest frequency value).
Kondo further discloses a position that is separated from the surface information (see at
least para. [0079] – [0080] of Kondo which discloses “the mesh ID is also separately created as column information, and the created column information is managed as information to be stored in the entry link 501 and the exit link 502. In other words, information required for uniquely identifying the link may all be stored in the entry link 501 and the exit link 502” and “FIG. 9 is a processing flowchart showing the processing of the route estimation unit 212. In FIG. 9, the route estimation unit 212 estimates the route between the departure place (entry link) and the destination (exit link) from the travel history 213 by using the departure link (provisional departure link) and the arrival link estimated by the destination estimation unit 209”, *Examiner interprets this as evidence of positions that are separated from the surface information).
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to further modify the information provider of Hosokawa, as modified by Kondo and Herlocker, to include a position that is separated from the surface information, as further taught by Kondo with a reasonable expectation of success in order to facilitate more effective collection of position information.
Regarding amended claim 6, Hosokawa discloses An information providing method (see at
least para. [0035] of Hosokawa which discloses “the subsystem 200 may provide notification about the event information” and see at least para. [0049] of Hosokawa which discloses “the receiving section 150 may receive car probe data from each mobile object 10 as the information”) that is performed by a computer (see at least para. [0186] of Hosokawa which discloses “a computer configured to perform the foregoing operations, according to an embodiment of the present invention”), the method comprising: a receiving step comprising: receiving (Fig. 3, 150 and see at least para. [0040] of Hosokawa which discloses ”a receiving section 150”), via a communication unit (see at least para. [0051] of Hosokawa which discloses “The receiving section 150 may communicate with the plurality of mobile objects 10 and receive the car probe data of each mobile object 10, via the Internet 40. The receiving section 150 may receive the car probe data of the plurality of mobile objects 10 through wireless communication, a subscriber network, a cellular network, or any desired combination of network”, *Communication through such networks corresponds to the claimed communication unit through which the receiver obtains the transmitted information), consecutive position information (see at least para. [0047] of Hosokawa which discloses “the position information of the mobile object 10” and see at least para. [0049] of Hosokawa which discloses “The receiving section 150 may be operable to receive information transmitted from each of a plurality of mobile objects 10. Each mobile object 10 may transmit information at designated time intervals, and the receiving section 150 may sequentially receive this transmitted information”, *Transmission of position information at designated time intervals and sequential reception of the transmitted probe data corresponds to receiving consecutive position information at predetermined time intervals as broadly as recited) at predetermined time intervals (see at least para. [0049] of Hosokawa which discloses “Each mobile object 10 may transmit information at designated time intervals”) from each of a plurality of mobile objects, along with a mobile object ID (see at least para. [0083] of Hosokawa which discloses “the ID of the mobile object based on the calculation using the ID. Then, the mobile object server may provide the object server managing the identified object agent with the setting data including the position information, the ID of the mobile object, and ID(s) of passenger(s) of the mobile object via the gateway apparatus”) and time information, and accumulating the received position information and time information as data keyed by the mobile object ID (see at least para. [0048] of Hosokawa which discloses “The determining section 146 may store the position information of this mobile object 10 and/or information of the determined region in the storage section 142, in association with this mobile object 10. The determining section 146 may store a history of the position information of this mobile object 10 and/or a history of the determined mobile object server 220 in the storage section 142”, *Storing a history of the position information corresponds to accumulating the received position information over time and Hosokawa further discloses that the stored information is associated with the mobile object, which corresponds to storing the accumulated position information as data keyed by the mobile ID) in a position information database (see at least para. [0127] of Hosokawa which discloses “The mobile object database 2300 may store the reliability with which each of a plurality of mobile objects 10 moving in a geographic space detects an event (referred to as the detection reliability). For example, the mobile object database 2300 may store the detection reliability of each mobile object 10 in association with each of the plurality of mobile objects 10. Furthermore, the mobile object database 2300 may store the detection reliability of each mobile object 10 in association with each of the one or more sensors 11 of the mobile object 10”, *Since Hosokawa also discloses a mobile object database that stores information associated with each mobile object, this corresponds to the claimed position information database under the broadest reasonable interpretation); a storing step (Fig. 3, 142 and see at least para. [0045] of Hosokawa which discloses “The storage section 142 may be operable to communicate with the dividing section 130 and store information concerning the plurality of first regions and the plurality of second regions”, *Examiner interprets the information on the regions to be map information) of storing map information (see at least para. [0138] of Hosokawa which discloses “map information of the geographic space possessed by the one mobile object 10”) that includes a road map (see at least para. [0041] of Hosokawa which discloses “The acquiring section 110 may be operable to acquire map data corresponding to the geographical areas where a mobile object 10 is positioned, from an external database 30, for example. In response to the map being updated, the acquiring section 110 may acquire some or all of the updated map data. The acquiring section 110 may be operable to acquire the map data from the Internet, a subscriber network, a cellular network, or any desired combination of networks. The system 100 may be operable to store the map data”, *Examiner interprets the map data of the geographical areas to be a road map).
Hosokawa does disclose based on a position information database (see at least para.
[0128] of Hosokawa which discloses “The mobile object database 2300 may store statistical information of detection results of events/ candidate events by the plurality of mobile objects 10”) in which time-discretely (see at least para. [0049] of Hosokawa which discloses “Each mobile object 10 may transmit information at designated time intervals, and the receiving section 150 may sequentially receive this transmitted information”) varying position information (see at least para. [0047] of Hosokawa which discloses “The determining section 146 may be operable to communicate with the storage section 142, and determine one region from the plurality of regions (e.g., regions A-F of FIG. 1) in which each of the mobile objects 10 is located based on the position information of the mobile object 10 and geographic information of the plurality of regions. The determining section 146 may identify a route or position in the map area managed by the system 100 that corresponds to the position information of the mobile object 10” and see at least para. [0036] of Hosokawa which discloses “the region corresponding to the position of the mobile object 10 might change” and see at least para. [0131] of Hosokawa which discloses “The dynamic map may be a high-definition digital geographic map that incorporates not only information concerning geographic objects, but also event information that changes over time, such as accidents, traffic jams, and construction regulations”, *Examiner interprets this as the position information changing over time, *This corresponds to accumulating position information over time per mobile object in a database (car probe data, histories per object), so it supports the “position information … varying over discrete time intervals .. accumulate” aspect (see at least para. [0036] of Hosokawa which discloses “the region corresponding to the position of the mobile object 10 might change” and see at least para. [0131] of Hosokawa which discloses “The dynamic map may be a high-definition digital geographic map that incorporates not only information concerning geographic objects, but also event information that changes over time, such as accidents, traffic jams, and construction regulations”, *Examiner interprets this as the position information changing over time); for each of the mobile objects during a predetermined period (see at least para. [0049] of Hosokawa which discloses “The receiving section 150 may be operable to receive information transmitted from each of a plurality of mobile objects 10. Each mobile object 10 may transmit information at designated time intervals, and the receiving section 150 may sequentially receive this transmitted information. In this embodiment, the receiving section 150 may receive car probe data from each mobile object 10 as the information. The car probe data may include information detected by the mobile object 10, such as position information of the mobile object 10”), for each of a plurality of mobile objects is accumulated (see at least para. [0048] of Hosokawa which discloses “The determining section 146 may store a history of the position information of this mobile object 10 and/or a history of the determined mobile object server 220 in the storage section 142” and see at least para. [0137] of Hosokawa which discloses “the mobile object server 220 may calculate the MPP of one mobile object 10. For example, the mobile object server 220 may calculate the MPP using, in addition to the current travel history of the one mobile object 10, at least one of pattern matching that utilizes the travel history up to the most recent travel history for the one mobile object 10, the travel state of another mobile object 10 at the current time point, and the current time range, day of the week, and the like”).
Hosokawa may not explicitly disclose during a period from a start time to a stop time of the
mobile object.
However, Hosokawa does teach continuous probe acquisition because Hosokawa already
acquires sequences of probe data over time at designated intervals while the mobile object moves, and stores them per mobile object (see at least para. [0152] of Hosokawa which discloses “a case in which detection results from a plurality of mobile objects 10 are received continuously in a short time for an unknown event/candidate event”. Hosokawa further discloses that each mobile object transmits information at designated time intervals while the mobile object is traveling, and the receiving section sequentially receives this transmitted information, thereby accumulating time-series probe data per mobile object.
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention, in view of Hosokawa’s continuous acquisition of per vehicle probe data, to treat the period between a vehicle start (i.e., ignition on/departure) and a vehicle stop (engine off/parking) as a “trip” and to regard the probe data collected during that trip as being received during a period from a start time to a stop time of the mobile object, since such start/stop based trip segmentation is a routine and widely used practice in vehicle telematics.
Hosokawa may not explicitly disclose a departure/arrival point position information
generating step comprising: calculating, for each of the mobile objects during a predetermined period, a highest frequency value associated with departure/arrival point position information, wherein the departure/arrival point position is defined as a position where the mobile object parked during travel and subsequently departed after parking; and generating, as departure/arrival point position information for the mobile object; surface information including a position corresponding to the highest frequency value; a position information outputting step comprising: for each of a plurality of mobile objects, outputting a travel route from a departure point position to an arrival point position; determining whether the departure point position or the arrival point position corresponds to a most frequent departure or arrival location of the mobile object; outputting the surface information including a position corresponding to a highest frequency value.
However, Kondo discloses a departure/arrival point position information generating step
(see at least para. [0036] of Kondo which discloses “the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination” and see at least para. [0073] of Kondo which discloses “the destination estimation unit 209 sets the point ID designated by the arrival place determination processing unit 206 (point ID transferred from the arrival place determination processing unit 206) as the departure point ID (S301), and then acquires the most frequent destination point ID among the departure point IDs from the departure place/destination table 210 (S302). In other words, in step S302, the destination estimation unit 209 selects the destination point ID in which the information of the number of times 403 is most frequent among the departure point IDs set in step S301 from the departure place/destination table 210” and see at least para. [0085] of Kondo which discloses “the route estimation unit 212 estimates the most frequent route from the designated “departure link” to the arrival link”) comprising: calculating (see at least para. [0074] of Kondo which discloses “calculating the most frequent destination point), a highest frequency value (see at least para. [0073] of Kondo which discloses “Thus, when calculating the most frequent destination point ID the number of times of the same destination point ID is totaled, and the departure point ID of the most frequent number of times is selected”) associated with departure/arrival point position information (see at least para. [0085] of Kondo which discloses “the route estimation unit 212 estimates the most frequent route from the designated “departure link” to the arrival link, sets the route that was estimated as the estimated route (S404), and thereafter ends the processing of this routine. In other words, in step S404, the most frequent route from the set departure link to the arrival link is estimated, and the route that was estimated is set as the estimated route. When, estimating the most frequent route, foremost, the departure link is designated as the entry link, and the ID of the exit link 502 in which the information of the number of times 503 is most frequent is acquired. Furthermore, with such exit link as the departure link, the ID of the exit link in which the information of the number of times 503 is most frequent is acquired, and this process is repeated from the “departure link” to the arrival link to trace the exit link in which the information of the number of times 503 is most frequent in order to estimate the most frequent route”) wherein the departure/arrival point position is defined as a position where the mobile object parked during travel and subsequently departed after parking (*Kondo discloses that route and frequency information are associated with departure and arrival links, which correspond to departure/arrival point position information. In particular, para. [0085] of Kondo describes a route estimation unit 212 that “estimates the most frequent route from the designated “departure link” to the arrival link” and when estimating the most frequent route, repeatedly selects from a table, the exit link whose number of time value is most frequent from the departure link to the arrival link. Therefore, Kondo teaches route and frequency information associated with departure and arrival positions on the map. Additionally, Kondo stores parking information as a history of the vehicle having parked in an area near a destination, and uses these parking positions are arrival (and departure) points, corresponding to positions where the vehicle parked during travel and subsequently departed after parking); and generating, as departure/arrival point position information for the mobile object (see at least para. [0036] of Kondo which discloses “the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination” and see at least para. [0073] of Kondo which discloses “the destination estimation unit 209 sets the point ID designated by the arrival place determination processing unit 206 (point ID transferred from the arrival place determination processing unit 206) as the departure point ID (S301), and then acquires the most frequent destination point ID among the departure point IDs from the departure place/destination table 210 (S302). In other words, in step S302, the destination estimation unit 209 selects the destination point ID in which the information of the number of times 403 is most frequent among the departure point IDs set in step S301 from the departure place/destination table 210” and see at least para. [0085] of Kondo which discloses “the route estimation unit 212 estimates the most frequent route from the designated “departure link” to the arrival link”), surface information (see at least para. [0036] of Kondo which discloses “the information of the point from the point information table 207, refers to the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination“) including a position corresponding to the highest frequency value (see at least para. [0073] of Kondo which discloses “Thus, when calculating the most frequent destination point ID the number of times of the same destination point ID is totaled, and the departure point ID of the most frequent number of times is selected”), a position information outputting step (see at least para. [0108] of Kondo which discloses “output guidance information as information which guides the vehicle based on the recommendation information 215 and which includes at least a parking position in the parking lot. The recommendation unit 214 can thereby guide the vehicle (driver) to the parking position based on the guidance information when the vehicle arrives at the facility”, *Examiner interprets this output of guidance information to be the position information outputter) comprising: for each of a plurality of mobile objects, outputting a travel route (see at least para. [0039] of Kondo which discloses “The route estimation unit 212 estimates the route to the destination estimated by the destination estimation unit 209. Here, the route estimation unit 212 estimates the route to the destination by using the travel history 213”) from a departure point position to an arrival point position (Kondo discloses outputting a travel route from a departure point position to an arrival point position. In particular, a route estimation unit 212 estimates the most frequent route from the designated departure link to the arrival link based on frequency information in a table and sets that route as the estimated route for output. The departure link corresponds to the departure point position (parking area entrance/departure place), and the arrival link corresponds to the arrival point position (destination parking area), thereby teaching output of a travel route from a departure point position to an arrival point position for the vehicle/mobile object); determining whether the departure point position or the arrival point position (see at least para. [0033] of Kondo which discloses “whether the vehicle has arrived at the entrance of the facility including the parking lot in the vicinity of the destination of the vehicle based on the positron information (position information based on the positioning of the positioning sensor 103) indicating the position of the vehicle on the map”) corresponds to a most frequent departure or arrival location of the mobile object (see at least para. [0070] of Kondo which discloses “The point ID of the departure point ID 401 and the point ID of the destination point ID 402 store information (for example, “1” to “5”) existing in the point ID 301 of the point information table 207. When referring to the information of each point ID, information of the corresponding point ID is acquired from the point information table 207”, *Kondo discloses determining whether the departure point position or arrival point position corresponds to a most frequent departure or arrival location. When a vehicle arrives at a parking area entrance (departure point ID), the destination estimation unit 209 sets that point as the departure point ID and then “acquires the most frequent destination point ID amount the departure point IDs from the departure place/destination table 210” by selecting the destination with the highest “number of times” value. This determines whether the current arrival destination corresponds to a most frequent arrival location for the vehicle based on its historical departure/destination table. The route estimation unit then confirms by estimating the most frequent route from the departure to that arrival point); outputting the surface information (see at least para. [0036] of Kondo which discloses “the information of the point from the point information table 207, refers to the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination“) including a position corresponding to a highest frequency value (see at least para. [0073] of Kondo which discloses “Thus, when calculating the most frequent destination point ID the number of times of the same destination point ID is totaled, and the departure point ID of the most frequent number of times is selected”).
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the method of Hosokawa to include a departure/arrival point position information generating step comprising: calculating, for each of the mobile objects during a predetermined period, a highest frequency value associated with departure/arrival point position information, wherein the departure/arrival point position is defined as a position where the mobile object parked during travel and subsequently departed after parking; and generating, as departure/arrival point position information for the mobile object; surface information including a position corresponding to the highest frequency value; a position information outputting step comprising: for each of a plurality of mobile objects, outputting a travel route from a departure point position to an arrival point position; determining whether the departure point position or the arrival point position corresponds to a most frequent departure or arrival location of the mobile object; outputting the surface information including a position corresponding to a highest frequency value; as taught in Kondo with a reasonable expectation of success in order to leverage established travel history analysis for accurate original/destination prediction in statistical mobility systems. This modification provides the predictable benefit of higher accuracy in statistical route outputs while Hosokawa’s surface generation ensures individual privacy protection, addressing both data utility and privacy concerns in mobility datasets.
Hosokawa, as modified by Kondo does disclose determining most frequent destinations
based on frequency values. In particular, see at least para. [0073] of Kondo which discloses “Thus, when calculating the most frequent destination point ID the number of times of the same destination point ID is totaled, and the departure point ID of the most frequent number of times is selected”, *This corresponds to using a highest frequency value (most frequent number of times) for departure/destination combinations).
Hosokawa in view of Kondo may not explicitly disclose estimating the position
corresponding to the highest frequency values represents a location near the residence of the user of the mobile object.
However, Herlocker (US2018/0268168) discloses estimating the position corresponding to
the highest frequency values represents a location near the residence of the user of the mobile object (see at least para. [0015] of Herlocker which discloses “a user's trip from home to work can be represented in telemetry data by a single trace. In this example, the first point of the associated trace is associated with the location of the user's home and the last point of the trace associated with the user's work. The path taken from the user's home to the user's work can be represented in a series of intermediate points between the first and last points of the trace and one or more links between adjacent points of the trace. As each trace represents a single trip, many traces for a single device may be collected in a single day and many more over a longer period. For example, over a period of a month, twenty traces may be collected for a user's trips from home to work. Because telemetry data often includes a time stamp, a trace will also in many cases be indicative of what time the user of the device left home and when the user arrived at work”).
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the claimed information provider of Hosokawa, as modified by Kondo, to estimate that the position corresponding to the highest frequency value represents a location near the residence of the user of the mobile object, as taught in Herlocker with a reasonable expectation of success in order to facilitate the output of only surface information, i.e., an obfuscated area and position information of points a t least a predetermined distance away from that position, in order to protect the user’s personal data by preventing third parties from inferring the precise location of the user’s home or other sensitive endpoints from shared trajectory data, while still enabling analysis of routes and stay positions as taught in Herlocker’s anonymization of geographic rout trace endpoints. See para. [0016]-[0017] for motivation.
Hosokawa, as modified by Kondo may not explicitly disclose in place of the highest
frequency position information, the surface information being configured so that the location near the residence of the user cannot be estimated; in response to the determination, replacing the corresponding departure and/or arrival point position information with surface information representing the most frequent departure or arrival location; outputting position information of a position that is separated by a predetermined distance or greater from the position having the highest frequency value, and of subsequent positions following said position; and enabling analysis including a movement route and stay positions of the mobile object.
However, Herlocker discloses in place of the highest frequency position information, the
surface information being configured so that the location near the residence of the user cannot be estimated (see at least para. [0047] of Herlocker which discloses “the client device associated with the first trace 202 could be associated with a user living at the address associated with the first origin point 206 based at least in part on the first trace 202. Therefore, in some embodimnts, certain sections of received traces may be removed to obfuscate the original origin 206 and destination 208 points of a trace or other relevant sections of the trace … The first cutoff 214 divides the first origin section 218 containing the first origin point 206 from the remainder of the trace 202. That is, the first origin cutoff 214 divides the points of telemetry data associated with the first trace 202 into two sections, the first origin section 218 and a section comprising the remaining points associated with the trace. In the embodiment of FIG. 2A, the first origin section 218 includes multiple points (including the first origin point 206) and connections between points. In some implementations, the section containing the origin point 206 (in this case the first origin section 218) is discarded, thereby obscuring the original origin point of the trace. In this way, it can be more difficult to determine personal user information such as a user's home using trace data including the first trace 206 or the second trace 204. This process can be repeated to generate a first destination cutoff, then determine and discard a destination section including the first destination point 208 to obscure the original destination of the first trace 202” , *Instead of outputting the exact origin/destination points, Herlocker discards the origin section (including origin point 206) and destination section (including destination point 208), thereby replacing the exact home/work position information with cropped traces from which “it can be more difficult to determine personal user information such as a user’s home” – see at least para. [0047] of Herlocker); in response to the determination, replacing the corresponding departure and/or arrival point position information with surface information representing the most frequent departure or arrival location (see at least para. [0047] of Herlocker which discloses “the first origin section 218 includes multiple points (including the first origin point 206) and connections between points. In some implementations, the section containing the origin point 206 (in this case the first origin section 218) is discarded, thereby obscuring the original origin point of the trace. In this way, it can be more difficult to determine personal user information such as a user's home using trace data including the first trace 206 or the second trace 204. This process can be repeated to generate a first destination cutoff, then determine and discard a destination section including the first destination point 208 to obscure the original destination of the first trace 202”, *Herlocker teaches replacing departure arrival position information (origin/destination points) with information representing those locations in anonymized form. While Herlocker describes discarding the origin section (including origin point 206) and destination section (including destination point 208) from the original trace, the result is an anonymized trace that represents the same frequent departure/arrival locations (home/work endpoints) without revealing their exact positions. A person of ordinary skill in the art would understand that outputting the anonymized trace in place of the full trace with exact endpoints constitutes replacing the precises departure/arrival position information with a representation (the cropped trace) of those locations); outputting position information of a position that is separated by a predetermined distance or greater from the position having the highest frequency value, and of subsequent positions following said position (Herlocker teaches outputting position information of positions separated by a predetermined distance or greater from the highest-frequency endpoint positions (origin/destination = home/work), and subsequent positions following those endpoints. See at least para. [0046] of Herlocker which discloses “The first trace 202 comprises a first origin point 206 and a first destination point 208 connected by a plurality of intermediate points. The first origin point 206 and the first destination point 208 represent the starting and ending locations, respectively, for a trip associated with the trace”). Herlocker discards the origin section (multiple points including origin point 206) and destination section (multiple points including destination point 208) from the trace, based on sectioning criteria, and outputs only the intermediate anonymized trace (positions beyond the cutoff distance from endpoints, and subsequent positions along the route). The cutoff effectively defines a predetermined distance threshold from the origin/destination (highest-frequency positions), beyond which the subsequent route positions are output, as claimed); and enabling analysis including a movement route and stay positions of the mobile object (see at least para. [0047] of Herlocker which discloses “trace data can be used to determine personal information about the associated user, for example the locations of the user's home, workplace, and other significant locations visited by the user”, *Examiner interprets this determination of personal data to correspond to movement route and stay position analysis. Such analysis of trace data necessarily involves analyzing the sequence of locations visited by the user and identifying locations where the user remains, which corresponds to analysis of movement routes and stay positions of the mobile object), while ensuring protection of position information associated with personal data of a user of the mobile object (see at least para. [0047] of Herlocker which discloses “the first origin section 218 includes multiple points (including the first origin point 206) and connections between points. In some implementations, the section containing the origin point 206 (in this case the first origin section 218) is discarded, thereby obscuring the original origin point of the trace. In this way, it can be more difficult to determine personal user information such as a user's home using trace data including the first trace 206 or the second trace 204. This process can be repeated to generate a first destination cutoff, then determine and discard a destination section including the first destination point 208 to obscure the original destination of the first trace 202”, *Examiner interprets that this anonymization process makes it more difficult to determine personal user information such as a user’s home using trace data, thereby ensuring protection of position information associated with personal data while enabling analysis of the preserved movement route data).
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to further modify the system of Hosokawa, as modified by Kondo, to include in place of the highest frequency position information, the surface information being configured so that the location near the residence of the user cannot be estimated; in response to the determination, replacing the corresponding departure and/or arrival point position information with surface information representing the most frequent departure or arrival location; outputting position information of a position that is separated by a predetermined distance or greater from the position having the highest frequency value, and of subsequent positions following said position; and enabling analysis including a movement route and stay positions of the mobile object;as taught in Herlocker with a reasonable expectation of success in order to protect user privacy by obfuscating the precise location of the user’s home or other sensitive endpoints in shared trajectory data, thereby preventing third parties from inferring personal information such as a user’s residence while still enabling the analysis and sharing of movement routes and stay positions for fleet management, navigation improvement, and traffic analytics and in order to enable analysis of vehicle movement patterns while reducing the risk of exposing sensitive user location information such as home or frequently visited locations. See para. [0047] of Herlocker for motivation.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Hosokawa (US 2020/0184820A1) in view of Kondo (US 2021/0348936 A1) in view of Herlocker (US 2018/0268168A1)and further in view of Yamashita (US 2020/0132500A1).
Regarding claim 5, Hosokawa, as modified by Kondo and Herlocker discloses wherein the
position information outputter (see at least para. [0108] of Kondo which discloses “output guidance information as information which guides the vehicle based on the recommendation information 215 and which includes at least a parking position in the parking lot. The recommendation unit 214 can thereby guide the vehicle (driver) to the parking position based on the guidance information when the vehicle arrives at the facility”, *Examiner interprets this output of guidance information to be the position information outputter) is configured to output (see at least para. [0188] of Hosokawa which discloses “the image data to be displayed on the display device 2080”, *Examiner interprets this display as further evidence of an output), the surface information (see at least para. [0036] of Kondo which discloses “the information of the point from the point information table 207, refers to the frequency information of the departure place and destination from the departure place/destination table 210, and estimates the next destination“) and the position information (see at least para. [0006] of Kondo which discloses “an arrival place determination processing unit which determines, based on position information indicating a position of a vehicle on a map”) of the positions that are separated by the predetermined distance (see at least para. [0029] of Kondo which discloses “determination unit 202 determines whether the vehicle has stopped by setting a constant value to the vehicle speed or the travel distance of the vehicle, such as when the vehicle speed is near 0 for a fixed period of time or when there is hardly any movement in the position of the vehicle (there is hardly any travel distance of the vehicle) from the position information”, *Examiner interprets set value of the travel distance to be a predetermined distance) or greater, from the position that has the highest frequency value (see at least para. [0073] of Kondo which discloses “Thus, when calculating the most frequent destination point ID the number of times of the same destination point ID is totaled, and the departure point ID of the most frequent number of times is selected”), and subsequent positions following the position (see at least para. [0085] of Kondo which discloses “the route estimation unit 212 estimates the most frequent route from the designated “departure link” to the arrival link, sets the route that was estimated as the estimated route (S404), and thereafter ends the processing of this routine. In other words, in step S404, the most frequent route from the set departure link to the arrival link is estimated, and the route that was estimated is set as the estimated route. When estimating the most frequent route, foremost, the departure link is designated as the entry link, and the ID of the exit link 502 in which the information of the number of times 503 is most frequent is acquired. Furthermore, with such exit link as the departure link, the ID of the exit link in which the information of the number of times 503 is most frequent is acquired, and this process is repeated from the “departure link” to the arrival link to trace the exit link in which the information of the number of times 503 is most frequent in order to estimate the most frequent route”).
Hosokawa, as modified by Kondo, may not explicitly disclose an output in a superimposed
manner on the map information.
However, in the same field of endeavor, Yamashita discloses an output in a superimposed
manner on the map information (see at leas para. [0005] of Yamashita which discloses “the selected group of the target probe information pieces are superimposed on the map. The group of the target probe information pieces having the above features will suggest a high possibility that a new road not reflected on the map has been opened”).
It would have been obvious to one of ordinary skill in the art before the effective filing date
of the claimed invention to modify the information provider of Hosokawa, as modified by Kondo and Herlocker, to include an output in a superimposed manner on the map information, as taught in Yamashita with a reasonable expectation of success in order to effectively provide an information provider and an information providing method that are capable of generating position information of a mobile object. See at least para. [0005] of Yamashita for motivation.
Additional Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Uchinoumi (US 20170309056A1) discloses , a translucent detailed three-dimensional map is superimposed and drawn on the simple three-dimensional map within the transparent drawing range in the vicinity of the boundary between the detailed three-dimensional map and the simple three-dimensional map. Therefore, in the entire displayed three-dimensional map, the both are visually recognized to be integrated without a sense of discomfort, whereby appearance of the three-dimensional map can be improved. Doi (JP2003315076A) discloses based on the route information and the road map information around the departure / arrival points, the movement route creation unit 4 first determines the departure / arrival station on the set route around the departure / arrival point (the nearest station to get on / off the train or bus) Or stop) (step S10) and the route from the departure place to the departure station and the route from the arrival station to the destination are created and stored (step S108). Next, the movement route creation unit 4 creates a plurality of routes between the departure and arrival stations selected in step S107 based on the route information, and the routes between the departure and arrival stations and the routes between the departure place and the departure station and the arrival stations.
Conclusion
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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/DANA D IVEY/Examiner, Art Unit 3662
/D.D.I/March 19, 2026
/JELANI A SMITH/Supervisory Patent Examiner, Art Unit 3662