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 .
Status of Claims
Claims 45-64 are pending in this application.
Claims 45, 54, 58, 60 and 61 are presented as currently amended claims.
No claims are newly presented.
No claims are cancelled.
Examiner's Note
Examiner has cited particular paragraphs / columns and line numbers or figures in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Applicant is reminded that the Examiner is entitled to give the broadest reasonable interpretation to the language of the claims. Furthermore, the Examiner is not limited to Applicants’ definition which is not specifically set forth in the claims.
Lead inventor of applied prior art JP 4130828 B2 is alternatively listed as Yoshioka Mototaka and as Kudo Takahiro depending on the publication source. Both inventors are listed in the pre-grant publication (JP 2006053132 A) and the grant publication (JP 4130828 B2). For clarity, the reference will be referred to as Yoshioka herein to be consistent with Applicant’s use and the Espacenet publication. The change of reference name is not a change in the art applied.
Claim Interpretation
The “set of locations” referenced in the limitations reciting “. . . determining, by the user device, a set of weights for the locations, each weight of the set of weights corresponding to a location of the set of locations, and each weight being based at least in part on a time since the respective locations were identified” has been interpreted to be an intermediate waypoint or final destination because the modifying phrase “identified at least periodically by the user device” appears to require a particular selection of locations as opposed to merely most time-recent GPS geolocations calculated. Consequently, the limitation “set of weights corresponding to an associated location of the set of locations” has been interpreted to be a set of weights associated with a midpoint waypoint destination, not a set of weights applied to a time-series of most-recent GPS geolocations while approaching a particular midpoint waypoint destination.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 45-55, 57-59, and 61 are rejected under 35 U.S.C. 103 as being unpatentable over Beaurepaire (US 20200240808 A1) in view of Yoshioka (JP 2006053132 A) (the combination of which is referred to as “combination Beaurepaire” hereinafter). As regards the individual claims:
Regarding claim 45, Beaurepaire teaches a computer-implemented method, comprising:
maintaining, by a user device, navigation (Beaurepaire: ¶ 048; "candidate parking locations can then be provided to routing engine 403 (e.g., any navigation routing engine known in the art or equivalent) to determine a route") to a first intermediate waypoint, the first intermediate waypoint corresponding to a multi-waypoint route on a map, the multi-waypoint route having one or more intermediate waypoints and a destination; (Beaurepaire: ¶ 056; "generating a route from A to C with a stopover a B") determining, by the user device, whether the user device is within a zone corresponding to the first intermediate waypoint of the multi-waypoint route; (Beaurepaire: ¶ 004; "apparatus is also caused to process map data representing a road network within a proximity threshold of the current destination to determine the recommended vehicle parking and/or stopping location") in response to determining that the user device is within the zone corresponding to the first intermediate waypoint, (Beaurepaire: ¶ 060; "upon arrival at destination A, approaching destination A within a threshold distance, or at the start of navigation to destination A, the routing platform 111 computes the best or optimized route (e.g., best with respect to travel time, distance, etc.) to destination B considering the need to park near destination A. Based on this upfront route computation to destination B from the parking location at destination A, the routing platform 111 recommends the most suitable parking location/area or even the best side of street next to destination A") identifying a set of locations of the user device, each location of the set of locations identified at least periodically by the user device; (Beaurepaire: ¶ 034; "system 100 of FIG. 1 introduces a capability to leverage data on known or predicted next destinations (e.g., determined by manual input or a user's mobility graph that represents, for instance, the user's historical mobility data and patterns comprising GPS points or trajectories of a device associated with a person tracked over a time period)") . . . updating the multi-waypoint route (Beaurepaire: ¶ 040; "destination module 401 determines the next destination (or any number of subsequent locations) following a current destination specified by a user. In other words, the next destination is any location that the user wants or is predicted to travel to after reaching a current destination or location”) (Beaurepaire: ¶ 042; "recommendation module 405 interacts with the routing engine 403 to optimize a vehicle parking and/or stopping location at the current destination or location based on the determined next destination.”)
Beaurepaire does not explicitly teach: determining, by the user device, a set of weights for the set of locations, each weight of the set of weights corresponding to an associated location of the set of locations, and each weight being based at least in part on a time since the associated location was identified; determining, by the user device, a departure score based at least in part on the set of weights and the set of locations; [updating] . . . on the map based at least in part on the departure score; however, Yoshioka does teach:
determining, by the user device, a set of weights for the set of locations, each weight of the set of weights corresponding to an associated location of the set of locations, and each weight being based at least in part on a time since the associated location was identified (Yoshioka: ¶ 280; "departure place purchase behavior detection unit 8103 detects the departure place and the time at the departure place from the movement history accumulation unit") (Yoshioka: ¶ 249; "departure place stay time detection unit 7103 detects the stay time at the departure place based on the movement history (step S7702). The goal achievement determination unit 7105 refers to the reference stay time corresponding to the departure place category from the reference stay time accumulation unit 7104 (step S7703), and determines whether or not the goal has been achieved depending on whether the stay time at the departure place is shorter than the reference stay time") (Yoshioka: ¶ 283; "reference stay time may be automatically generated from the stay time of each category in the accumulated movement history.") (Yoshioka: ¶ 281; "[if the] alternative destination of the departure place is not predicted, and the process proceeds to step S7708 (step S7705). (At this time, the travel destination that is the same category as the departure place category may be excluded from the candidates, and the travel destination may be predicted from the travel history in the same manner as in the above") determining, by the user device, a departure score based at least in part on the set of weights and the set of locations; (Yoshioka: ¶ 280; "determines whether or not the goal has been achieved depending on whether the stay time at the departure place is shorter than the reference stay time. (Step S7704). If it is short, it is determined that the objective has not been achieved (yes in step S7704), and the process proceeds to step S7706. If it is long, it is determined that the objective has been achieved (yes in step S7705), and the process proceeds to step S7705.") [updating] . . . on the map based at least in part on the departure score. (Yoshioka: ¶ 282; "alternative destination search unit 7108 searches the map information storage unit 7107 for an alternative destination according to the determined destination category (step S7707). In step S7708, display control of the destination information predicted by the display control unit 7109 is performed. Then, the information presentation unit 7110 presents information") (Yoshioka: ¶ 281; "and the travel destination may be predicted from the travel history in the same manner as in the above embodiment to display the information.")
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Beaurepaire with the teachings of Yoshioka with a reasonable expectation of success because the use of a known technique to improve similar methods in the same way is obvious (KSR Int'l Co. v. Teleflex Inc., 550 U.S. at 417, 82 USPQ2d at 1396.) In the instant case, both Beaurepaire's and Yoshioka's base methods are similar multi-waypoint routing improvement methods; however, the combined device would be improved because Yoshioka’s teaching of a weighted mechanism that considers previous movement history to determine departure from a mid-waypoint would create a predictable expectation of advantage because doing so would make the results clearer to the user. Yoshioka: ¶ 007.
Regarding claim 46, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 45. Yoshioka further teaches:
wherein updating the multi-waypoint route includes maintaining navigation to the first intermediate waypoint based at least in part on the departure score in relation to a departure threshold. (Yoshioka: ¶ 280; "departure place category from the reference stay time accumulation unit 7104 (step S7703), and determines whether or not the goal has been achieved depending on whether the stay time at the departure place is shorter than the reference stay time. (Step S7704). If it is short, it is determined that the objective has not been achieved (yes in step S7704), and the process proceeds to step S7706. If it is long, it is determined that the objective has been achieved (yes in step S7705), and the process proceeds to step S7705.")
Regarding claim 47, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 45. Yoshioka further teaches:
wherein updating the multi-waypoint route includes advancing navigation from the first intermediate waypoint to a second intermediate waypoint or to the destination based at least in part on the departure score in relation to a departure threshold. (Yoshioka: ¶ 282; "alternative destination search unit 7108 searches the map information storage unit 7107 for an alternative destination according to the determined destination category (step S7707). In step S7708, display control of the destination information predicted by the display control unit 7109 is performed. Then, the information presentation unit 7110 presents information")
Regarding claim 48, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 45. Beaurepaire further teaches:
wherein the zone is a pre-arrival zone. (Beaurepaire: ¶ 046; "the proximity threshold applied by the recommendation module 405 can encompass areas before and/or after reaching the destination")
Regarding claim 49, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 48. Beaurepaire further teaches:
wherein the pre-arrival zone is based at least in part on an area having one or more area properties. (Beaurepaire: ¶ 060; "routing platform 111 can present a user interface with the parking location recommendation on arrival at the destination A, approaching destination A within a proximity threshold, at the start of navigation, etc.")
Regarding claim 50, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 49. Beaurepaire further teaches:
wherein the pre-arrival zone includes an area with an area property of being a parking area associated with the first intermediate waypoint. (Beaurepaire: ¶ 060; "routing platform 111 computes an optimized route to destination B from a recommended parking/stopping location at intermediate destination A. In one embodiment, upon arrival at destination A, approaching destination A within a threshold distance, or at the start of navigation to destination A, the routing platform 111 computes the best or optimized route (e.g., best with respect to travel time, distance, etc.) to destination B considering the need to park near destination A")
Regarding claim 51, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 48. Beaurepaire further teaches:
wherein the pre-arrival zone includes an area within a distance of the first intermediate waypoint. (Beaurepaire: ¶ 046-047; "the proximity threshold applied by the recommendation module 405 can encompass areas before and/or after reaching the destination. Data on distance to be walked can also be a parameter when determining an optimal parking or stopping location. For example, the recommendation module 405 can perform optimizations based on whether the user's profile and/or preferences data indicates that the user is ready to walk a configured distance (e.g., 200-300 meters),")
Regarding claim 52, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 48. Beaurepaire further teaches:
wherein the pre-arrival zone includes an area within a distance of one or more entries associated with the first intermediate waypoint. (Beaurepaire: ¶ 066; "routing platform 111 determines a plurality of shared vehicles within a proximity threshold of the current location of the user searching for a shared vehicle. For example, the routing platform 111 can query a mobility provider for the location of shared vehicles and present the locations on a mapping user interface.")
Regarding claim 53, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 48. Beaurepaire further teaches:
wherein the pre-arrival zone includes any combination of the following: an area within a distance of the first intermediate waypoint, (Beaurepaire: ¶ 060; "upon arrival at destination A, approaching destination A within a threshold distance, or at the start of navigation to destination A, the routing platform 111 computes the best or optimized route (e.g., best with respect to travel time, distance, etc.) to destination B considering the need to park near destination A. Based on this upfront route computation to destination B from the parking location at destination A, the routing platform 111 recommends the most suitable parking location/area or even the best side of street next to destination A") an area within a distance of an entry associated with the first intermediate waypoint, (Beaurepaire: ¶ 066; "routing platform 111 determines a plurality of shared vehicles within a proximity threshold of the current location of the user searching for a shared vehicle. For example, the routing platform 111 can query a mobility provider for the location of shared vehicles and present the locations on a mapping user interface.") an area within a distance of one or more entries associated with the first intermediate waypoint, and a parking area associated with the first intermediate waypoint. (Beaurepaire: ¶ 060; "routing platform 111 computes an optimized route to destination B from a recommended parking/stopping location at intermediate destination A. In one embodiment, upon arrival at destination A, approaching destination A within a threshold distance, or at the start of navigation to destination A, the routing platform 111 computes the best or optimized route (e.g., best with respect to travel time, distance, etc.) to destination B considering the need to park near destination A")
Regarding claim 54, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 45. Yoshioka further teaches:
wherein determining the departure score further based at least in part on a number of locations of the set of locations inside the zone (Yoshioka: ¶ 139; "the driver's current location and time, and information on the route to the current location are used, and the destination information prediction unit 2102 uses the accumulated information in the movement history accumulation unit") (Yoshioka: ¶ 006; "the movement destination display device according to the present invention includes movement history accumulation means for accumulating movement history, which is information relating to a movement route from a departure place")
Regarding claim 55, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 45. Yoshioka further teaches:
wherein the departure score corresponds, at least in part, to a ratio of a number of locations of the set of locations inside the zone compared to a total number of locations in the set of locations. (Yoshioka: ¶ 020; "t has passed the Δ △ intersection 100 times in the past, and then has reached the restaurant 40 times, has reached the convenience store 30 times, and has reached the supermarket 20 times. It is shown that. Further, the movement destination arrival probability is calculated as “movement destination arrival frequency ÷ total number of passages × 100 (%)”. In the case of the movement destination candidate list 201, the restaurant is 40% (40 ÷ 100 × 100), and similarly. It is calculated that the convenience store is 30% and the supermarket is 20%. This indicates that when a user is currently moving at a point that triggers prediction,")
Regarding claim 57, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 45. Yoshioka further teaches:
wherein the departure score corresponds, at least in part, to distances of the locations of the set of locations from the first intermediate waypoint. (Yoshioka: ¶ 139; "the driver's current location and time, and information on the route to the current location are used, and the destination information prediction unit 2102 uses the accumulated information in the movement history accumulation unit") (Yoshioka: ¶ 293; "departure place purchase behavior detection unit 8103 detects the departure place and the time at the departure place from the movement history accumulation unit") (Yoshioka: ¶ 006; "the movement destination display device according to the present invention includes movement history accumulation means for accumulating movement history, which is information relating to a movement route from a departure place")
Regarding claim 58, Beaurepaire teaches a device comprising:
a memory configured to store computer-executable instructions; and a processor configured to access the memory and execute the computer-executable instructions to at least: (Beaurepaire: ¶ 004; "comprises at least one processor, and at least one memory including computer program code") maintain, by the device, navigation to (Beaurepaire: ¶ 048; "candidate parking locations can then be provided to routing engine 403 (e.g., any navigation routing engine known in the art or equivalent) to determine a route") a first intermediate waypoint, the first intermediate waypoint corresponding to a multi-waypoint route on a map, the multi- waypoint route having one or more intermediate waypoints and a destination; (Beaurepaire: ¶ 056; "generating a route from A to C with a stopover a B") determine, by the device, whether the device is within a zone corresponding to the first intermediate waypoint of the multi-waypoint route; (Beaurepaire: ¶ 004; "comprises at least one processor, and at least one memory including computer program code") in response to determining that the device is within the zone corresponding to the first intermediate waypoint (Beaurepaire: ¶ 060; "upon arrival at destination A, approaching destination A within a threshold distance, or at the start of navigation to destination A, the routing platform 111 computes the best or optimized route (e.g., best with respect to travel time, distance, etc.) to destination B considering the need to park near destination A. Based on this upfront route computation to destination B from the parking location at destination A, the routing platform 111 recommends the most suitable parking location/area or even the best side of street next to destination A") identify a set of locations of the device, each location of the set of locations identified at least periodically by the device; (Beaurepaire: ¶ 034; "system 100 of FIG. 1 introduces a capability to leverage data on known or predicted next destinations (e.g., determined by manual input or a user's mobility graph that represents, for instance, the user's historical mobility data and patterns comprising GPS points or trajectories of a device associated with a person tracked over a time period)") . . . update the multi-waypoint route (Beaurepaire: ¶ 040; "destination module 401 determines the next destination (or any number of subsequent locations) following a current destination specified by a user. In other words, the next destination is any location that the user wants or is predicted to travel to after reaching a current destination or location”) (Beaurepaire: ¶ 042; "recommendation module 405 interacts with the routing engine 403 to optimize a vehicle parking and/or stopping location at the current destination or location based on the determined next destination.”)
Beaurepaire does not explicitly teach:
determine, by the device, a set of weights for the set of locations, each weight of the set of weights corresponding to an associated location of the set of locations, and each weight being based at least in part on a time since the associated location was identified; determine, by the device, a departure score based at least in part on the set of weights and the set of locations; [update] . . . on the map based at least in part on the departure score; however, Yoshioka does teach:
determine, by the device, a set of weights for the set of locations, each weight of the set of weights corresponding to an associated location of the set of locations, and each weight being based at least in part on a time since the associated location was identified; (Yoshioka: ¶ 280; "departure place purchase behavior detection unit 8103 detects the departure place and the time at the departure place from the movement history accumulation unit") (Yoshioka: ¶ 249; "departure place stay time detection unit 7103 detects the stay time at the departure place based on the movement history (step S7702). The goal achievement determination unit 7105 refers to the reference stay time corresponding to the departure place category from the reference stay time accumulation unit 7104 (step S7703), and determines whether or not the goal has been achieved depending on whether the stay time at the departure place is shorter than the reference stay time") (Yoshioka: ¶ 283; "reference stay time may be automatically generated from the stay time of each category in the accumulated movement history.") (Yoshioka: ¶ 281; "[if the] alternative destination of the departure place is not predicted, and the process proceeds to step S7708 (step S7705). (At this time, the travel destination that is the same category as the departure place category may be excluded from the candidates, and the travel destination may be predicted from the travel history in the same manner as in the above") determine, by the device, a departure score based at least in part on the set of weights and the set of locations; (Yoshioka: ¶ 280; "determines whether or not the goal has been achieved depending on whether the stay time at the departure place is shorter than the reference stay time. (Step S7704). If it is short, it is determined that the objective has not been achieved (yes in step S7704), and the process proceeds to step S7706. If it is long, it is determined that the objective has been achieved (yes in step S7705), and the process proceeds to step S7705.") [update] . . . on the map based at least in part on the departure score (Yoshioka: ¶ 282; "alternative destination search unit 7108 searches the map information storage unit 7107 for an alternative destination according to the determined destination category (step S7707). In step S7708, display control of the destination information predicted by the display control unit 7109 is performed. Then, the information presentation unit 7110 presents information") (Yoshioka: ¶ 281; "and the travel destination may be predicted from the travel history in the same manner as in the above embodiment to display the information.")
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Beaurepaire with the teachings of Yoshioka with a reasonable expectation of success because the use of a known technique to improve similar methods in the same way is obvious (KSR Int'l Co. v. Teleflex Inc., 550 U.S. at 417, 82 USPQ2d at 1396.) In the instant case, both Beaurepaire's and Yoshioka's base methods are similar multi-waypoint routing improvement methods; however, the combined device would be improved because Yoshioka’s teaching of a weighted mechanism that considers previous movement history to determine departure from a mid-waypoint would create a predictable expectation of advantage because doing so would make the results clearer to the user. Yoshioka: ¶ 007.
Regarding claim 59, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 58. Yoshioka further teaches:
wherein determining the departure score further based at least in part on an auto-advance tendency factor. (Yoshioka: ¶ 024; "operation candidate index may be stored as a rule in advance, or may be set by the user, or an item with a high frequency of operation may be automatically selected reflecting the user's operation history.")
Regarding claim 61, Beaurepaire teaches a device comprising:
non-transitory computer-readable media comprising computer-executable instructions that, when executed by one or more processors of a computer system, cause the computer system to perform operations, comprising: (Beaurepaire: ¶ 004; "comprises at least one processor, and at least one memory including computer program code") maintaining, by a user device, navigation (Beaurepaire: ¶ 048; "candidate parking locations can then be provided to routing engine 403 (e.g., any navigation routing engine known in the art or equivalent) to determine a route") to a first intermediate waypoint, the first intermediate waypoint corresponding to a multi-waypoint route on a map, the multi-waypoint route having one or more intermediate waypoints and a destination; (Beaurepaire: ¶ 056; "generating a route from A to C with a stopover a B") determining, by the user device, whether the user device is within a zone corresponding to the first intermediate waypoint of the multi-waypoint route; (Beaurepaire: ¶ 004; "apparatus is also caused to process map data representing a road network within a proximity threshold of the current destination to determine the recommended vehicle parking and/or stopping location") in response to determining that the user device is within the zone corresponding to the first intermediate waypoint, (Beaurepaire: ¶ 060; "upon arrival at destination A, approaching destination A within a threshold distance, or at the start of navigation to destination A, the routing platform 111 computes the best or optimized route (e.g., best with respect to travel time, distance, etc.) to destination B considering the need to park near destination A. Based on this upfront route computation to destination B from the parking location at destination A, the routing platform 111 recommends the most suitable parking location/area or even the best side of street next to destination A") identifying a set of locations of the user device, each location of the set of locations identified at least periodically by the user device; (Beaurepaire: ¶ 034; "system 100 of FIG. 1 introduces a capability to leverage data on known or predicted next destinations (e.g., determined by manual input or a user's mobility graph that represents, for instance, the user's historical mobility data and patterns comprising GPS points or trajectories of a device associated with a person tracked over a time period)") . . . updating the multi-waypoint route (Beaurepaire: ¶ 040; "destination module 401 determines the next destination (or any number of subsequent locations) following a current destination specified by a user. In other words, the next destination is any location that the user wants or is predicted to travel to after reaching a current destination or location”) (Beaurepaire: ¶ 042; "recommendation module 405 interacts with the routing engine 403 to optimize a vehicle parking and/or stopping location at the current destination or location based on the determined next destination.”)
Beaurepaire does not explicitly teach:
determining, by the user device, a set of weights for the set of locations, each weight of the set of weights corresponding to an associated location of the set of locations, and each weight being based at least in part on a time since the associated location was identified; a set of weights for the set of locations, each weight of the set of weights corresponding to an associated location of the set of locations, and each weight being based at least in part on a time since the associated location was identified; determining, by the user device, a departure score based at least in part on the set of weights and the set of locations; [updating]. . . on the map based at least in part on the departure score; however, Yoshioka does teach:
determining, by the user device, a set of weights for the set of locations, each weight of the set of weights corresponding to an associated location of the set of locations, and each weight being based at least in part on a time since the associated location was identified; (Yoshioka: ¶ 280; "departure place purchase behavior detection unit 8103 detects the departure place and the time at the departure place from the movement history accumulation unit") (Yoshioka: ¶ 249; "departure place stay time detection unit 7103 detects the stay time at the departure place based on the movement history (step S7702). The goal achievement determination unit 7105 refers to the reference stay time corresponding to the departure place category from the reference stay time accumulation unit 7104 (step S7703), and determines whether or not the goal has been achieved depending on whether the stay time at the departure place is shorter than the reference stay time") (Yoshioka: ¶ 283; "reference stay time may be automatically generated from the stay time of each category in the accumulated movement history.") (Yoshioka: ¶ 281; "[if the] alternative destination of the departure place is not predicted, and the process proceeds to step S7708 (step S7705). (At this time, the travel destination that is the same category as the departure place category may be excluded from the candidates, and the travel destination may be predicted from the travel history in the same manner as in the above") a set of weights for the set of locations, each weight of the set of weights corresponding to an associated location of the set of locations,; (Yoshioka: ¶ 280; "determines whether or not the goal has been achieved depending on whether the stay time at the departure place is shorter than the reference stay time. (Step S7704). If it is short, it is determined that the objective has not been achieved (yes in step S7704), and the process proceeds to step S7706. If it is long, it is determined that the objective has been achieved (yes in step S7705), and the process proceeds to step S7705.") [updating]. . . on the map based at least in part on the departure score (Yoshioka: ¶ 282; "alternative destination search unit 7108 searches the map information storage unit 7107 for an alternative destination according to the determined destination category (step S7707). In step S7708, display control of the destination information predicted by the display control unit 7109 is performed. Then, the information presentation unit 7110 presents information") (Yoshioka: ¶ 281; "and the travel destination may be predicted from the travel history in the same manner as in the above embodiment to display the information.")
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Beaurepaire with the teachings of Yoshioka with a reasonable expectation of success because the use of a known technique to improve similar methods in the same way is obvious (KSR Int'l Co. v. Teleflex Inc., 550 U.S. at 417, 82 USPQ2d at 1396.) In the instant case, both Beaurepaire's and Yoshioka's base methods are similar multi-waypoint routing improvement methods; however, the combined device would be improved because Yoshioka’s teaching of a weighted mechanism that considers previous movement history to determine departure from a mid-waypoint would create a predictable expectation of advantage because doing so would make the results clearer to the user. Yoshioka: ¶ 007.
Claims 52 and 62-63 are rejected under 35 U.S.C. 103 as being unpatentable over combination Beaurepaire as applied to claims 48 and 61 respectively above, and further in view of Chen (US 20090210146 A1).
Regarding claim 56, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 45. Neither combination Beaurepaire nor Chen explicitly teach:
wherein the departure score corresponds, at least in part, to distances of the locations of the set of locations from the zone; however, Yoshioka does teach:
A weighted arrival system where a distance from multiple destinations in the zone are considered when determining arrival (Yoshioka: ¶ 280-283; ¶ 249)
and Chen teaches:
A system in which distance from a destination is considered for determine departure(Chen: ¶ 063; "the processing module 12 of the system 1 detects departure from the visited place-of-interest (I) only when a current location of the processing module 12 of the system 1 is at least a predetermined distance, e.g., 10 kilometers, from the visited place-of-interest").
Therefore, before the effective filling date of the claimed invention a person of ordinary skill in the art would be taught or suggested:
wherein the departure score corresponds, at least in part, to distances of the locations of the set of locations from the zone.
because simple substitution of one known element for another to obtain predictable results is obvious (KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 416; MPEP § 2143(I)(B)). In the instant case, Yoshioka contains a method which differs from the claimed limitation by the substitution of applying distance to determining departure, but Chen shows that evaluating departure from a destination with distance was known in the art and one of ordinary skill in the art could have substituted one known element for another such that Kudos multiple location weighting was applied to Chen’s distance test and the results of the substitution would have been predictable. Consequently, the combination is obvious to a person of ordinary skill in the art.
Regarding claim 62, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 61. Combination Beaurepaire does not explicitly teach:
wherein the departure score is calculated at least periodically; however, Chen does teach: wherein the departure score is calculated at least periodically. (Chen: ¶ 064; "when the processing module 12 of the system 1 detects the departure from the visited place-of-interest (I), the flows proceeds to step 38. Otherwise, the flow goes back to step 36.").
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Beaurepaire with the teachings of Chen with a reasonable expectation of success because the use of a known technique to improve similar methods in the same way is obvious (KSR Int'l Co. v. Teleflex Inc., 550 U.S. at 417, 82 USPQ2d at 1396.) In the instant case, both Beaurepaire's and Chen's base methods are similar vehicle routing methods; however, the combined device would predictably be improved by more completely considering the amount of travel time required for multiple destinations (Chen: ¶ 005).
Regarding claim 63 as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 61. Neither combination Beaurepaire nor Chen explicitly teach:
wherein a period for identifying each location of the set of locations is one second; however, Chen does teach:
A system in which identifying each location of the set of locations is consistently repeated. (Chen: ¶ 064; "when the processing module 12 of the system 1 detects the departure from the visited place-of-interest (I), the flows proceeds to step 38. Otherwise, the flow goes back to step 36.").
Therefore, before the effective filling date of the claimed invention a person of ordinary skill in the art would be taught or suggested:
wherein a period for identifying each location of the set of locations is one second.
because routine optimization does not support the patentability of subject matter encompassed by the prior art unless there is evidence indicating the conditions are critical. MPEP § 2144.05 (II). Here, updating a navigational result once per second or ten times per second is not critical but is rather is a matter of a reduction to practice based on the amount of processor power and memory available to the system.
Claim 60 is rejected under 35 U.S.C. 103 as being unpatentable over combination Beaurepaire as applied to claim 58 above, and further in view of Ishibashi (JP 5076617 B2).
Regarding claim 60, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 58. Combination Beaurepaire does not explicitly teach:
wherein the departure score corresponds, at least in part, to a number of re-routes to the first intermediate waypoint after the user device entered the zone; however, Ishibashi does teach:
wherein the departure score corresponds, at least in part, to a number of re-routes to the first intermediate waypoint after the user device entered the zone. (Ishibashi: ¶ 039; "If the reroute occurs more than a predetermined number of times, route guidance is provided based on the recommended route to the destination that should have passed, even though it is actually going through the destination and moving to the next destination").
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Beaurepaire with the teachings of Ishibashi with a reasonable expectation of success because the use of a known technique to improve similar methods in the same way is obvious (KSR Int'l Co. v. Teleflex Inc., 550 U.S. at 417, 82 USPQ2d at 1396.) In the instant case, both Beaurepaire's and Ishibashi's base methods are similar multi-waypoint routing improvement methods; however, the combined device would be improved because Ishibashi’s teaching of an automatic recognition of leaving a location would create a predictable expectation of advantage because doing so would improve performance regardless if “the current position of the vehicle and the coordinates of the destination match, accurat[ly].” Ishibashi: ¶ 006.
Claim 64 is rejected under 35 U.S.C. 103 as being unpatentable over combination Beaurepaire as applied to claim 61 above, and further in view of Ogino (JP 2011234022 A)
Regarding claim 64, as detailed above, combination Beaurepaire teaches the invention as detailed with respect to claim 61. Combination Beaurepaire does not explicitly teach:
wherein the set of locations is limited to a maximum number of locations, an oldest location being replaced by a newest location.; however, Ogino does teach:
wherein the set of locations is limited to a maximum number of locations, an oldest location being replaced by a newest location. (Ogino: Pg. 003; "The location history table 121 stores the latest 25 location information, and is configured to delete the oldest location information when new location information acquired by the location information acquisition unit 11 is stored.").
Before the effective filling date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the teachings of Beaurepaire with the teachings of Ogino with a reasonable expectation of success because the use of a known technique to improve similar methods in the same way is obvious (KSR Int'l Co. v. Teleflex Inc., 550 U.S. at 417, 82 USPQ2d at 1396.) In the instant case, both Beaurepaire's and Ogino's base methods are similar navigation; however, the combined device would better manage memory reducing the cost of the device.
Response to Arguments
Applicant's remarks filed Sep. 22, 2025 have been fully considered.
Applicant’s argument and amendments with respect to the previous applied 35 U.S.C. § 112(b) rejection are persuasive and the rejection is hereby withdrawn.
Applicant's arguments and amendments filed Sep. 22, 2025 with respect to the previous applied 35 U.S.C. § 103 rejection have been fully considered but are not persuasive. Applicant argues that:
[applied prior art] does not explicitly teach 1) "determining, by the user device, a set of weights for the set of locations, each weight of the set of weights corresponding to an associated location of the set of locations, and each weight being based at least in part on a time since the associated location was identified," 2) "determining, by the user device, a departure score based at least in part on the set of weights and the set of locations," and 3) "updating the multi-waypoint route on the map based at least in part on the departure score." Office Action, page 6. For at least these reasons, Beaurepaire does not disclose, teach, or suggest (Applicant’s Arguments filed Sep. 22, 2025, pg. 10).
First, with respect to Applicant’s argument that independent claim’s limitation reciting “determining…a set of weights for the set of locations" is not taught a because the prior art uses a predicted amount of time at a destination. The independent claims use broad claim language such that “set of locations” has been interpreted to be a series of intermediate locations entered by the device user as destinations wherein a ‘time at a destination’ prediction would be a weighted value for predicting if the destination was 'reached' or ‘arrived at’ within the context of the claimed invention. For example, if a user had entered four destinations A through D, and the user spent two minutes at a destination B, where spending 70 minutes was typical, Yoshioka’s prediction of 2 minutes would be a weighed on a 70-point scale used to determine a score that destination B was specifically reached. Combined with Beaurepaire's multi-step routing process, a person of ordinary skill in the art would be taught or suggested the claimed limitation of “determining…a set of weights for the set of locations.”
Second and similarly, with respect to Applicant's argument that prior art fails to teach or suggest “determining, by the user device, a departure score based at least in part on the set of weights and the set of locations” because prior art only teaches a binary assessment of having arrived at a location, it is noted that Yoshioka’s ‘actual time at a destination’ versus Yoshioka’s ‘predicted time at destination’ is a weighted value being used to determine a departure score. Yoshioka applies the score to a single output of providing an alternative destination or not, an effective score of zero or one; however, a person of ordinary skill in the art would recognize that the raw relationship between the time spent at the destination and predicted time expected at the destination could be used to generate a more complex score, for example, by dividing time at the destination with expected time at the destination. In either case, the combination teaches “determining, by the user device, a departure score based at least in part on the set of weights and the set of locations”.
Third, with respect to Applicant's argument that prior art fails to teach or suggest “updating the multi-waypoint route on the map based at least in part on the departure score” because Yoshioka only presents an alternative destination when the target destination is not reached, as explained supra combining Beaurepaire's multi-step routing process with Yoshioka’s optional introduction of a new location based on a determination that the targeted destination was reached would teach “updating the multi-waypoint route on the map based at least in part on the departure score” to a person of ordinary skill in the art. The fact that Yoshioka only teaches updating a multi-destination routing under specific circumstances is consistent with Applicant’s claimed invention because the claimed invention would also only update the multi-point destination routing under specific circumstances, particularly when a destination was determined as ‘reached’ or ‘skipped’ based upon the “set of locations.”
Consequently, Applicant’s amendments and arguments with respect to the previous 35 U.S.C. § 103 rejection are not persuasive.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure Wong (US 9741191 B1) which discloses a method of arriving at a destination based on a threshold distance.
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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/C.P./Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663