DETAILED ACTION
This FINAL action is in response to Application No. 18/572,187 filed 12/20/2023, which claims priority from PCT/JP2022/022902 and JP2021-115468 filed 06/07/2022 and 07/13/2021. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . The amendment presented on 9/19/2025 which provides amendment to claims 1-5, is hereby acknowledged. Claims 1-5 are currently pending.
Claim Interpretation – Withdrawn
The previous interpretation of limitations within claims 1 and 4 as invoking 35.U.S.C. §112(f) has been withdrawn as necessitated by amendment.
Claim Rejections – Withdrawn
The previous 35 U.S.C §102 rejections of claims 1-5 have been withdrawn as necessitated by amendment.
The previous 35 U.S.C §112(a) rejections of claims 1-5 have been withdrawn as necessitated by amendment.
Response to Arguments
Applicant's arguments pertaining to the previous prior art rejection with respect to claims 1-5 have been considered, however, the amendment(s) to the claims necessitated a new consideration and search resulting in new prior art cited below.
In addition, issues under 35 U.S.C §112(b) remain, see the rejections below.
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 1-5 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1 (and similarly in claim 5), the metes and bounds of “predetermined range” is unclear. The claims and specification does not provide information on how the “predetermined range” is determined or what sort of measurement/distance it should be (See specification [0069], [0072]-[0073], [0075], [0078], [0084], [0095], [0104]). All of these portions of the specification make reference to “predetermined range” but provide no definition of what it is or how it is determined. In addition, it is not clear whether “a predetermined range” in line 18 is the same “predetermined range” from line 14 or if it is supposed to be a different “predetermined range”.
Regarding claim 2, it is not clear whether a “group of grids” is the same or different from the “plurality of grids” in claim 1.
Regarding claim 3, it is not clear whether “a grid” is the same or different from the “grid” from claim 1. Additionally, it is not clear how data points within a single grid “shift” from decreasing to increasing.
Dependent claims not mentioned inherit the deficiencies of their parent claims.
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.
Claim(s) 1, 2, 4, and 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dorum (US 2018/0364063 A1, from IDS received 12/20/2023), in view of Chowdhary (US 8,447,463 B1), and further in view of Penna et al. (US 2016/0364985 A1).
Regarding claim 1, Dorum teaches a parking lot information analysis device comprising:
a memory configured to store a program and map information including center position information of a plurality of facilities; and a processor configured to execute the program and control the parking lot information analysis device. More specifically, map database includes geographic data comprising parking lots (Dorum, [0031]).
receive consecutive positional information, together with time information, from each of a plurality of vehicles; More specifically, probe data which includes vehicle positional information and timing information is received by the mapping system (Dorum, [0034]).
determine that a vehicle has parked, when there is no change in its positional information for a predetermined period of time or more; stores the positional information as parking position information of the vehicle. More specifically, the speed (position over time) of the vehicle in the probe data allows the system to determine if the vehicle is parked (Dorum, [0042]).
…plot a plurality of pieces of parking position information into a plurality of grids within a predetermined range including center position information of one facility stored in the map information. More specifically, parking lot clusters are identified based on the probe data using techniques such as “mean shift” or “median shift”, which are used to find a center of mass for the parking lot clusters. A specified radius (range from center) is used in the calculations (Dorum, [0052]). The clusters are made up of grids (Dorum, [0054]). A final cluster requires a minimum number (value) of likely parking locations (Dorum, [0056]). Map data is updated with the determined parking lot boundary (Dorum, [0068]).
However, Dorum may not explicitly teach every aspect of
set a zone having a predetermined range including the center position information of one facility included in the map information; [and]
divide the zone into a plurality of grids;
Chowdhary discloses a parking lot is mapped digitally to display precise locations of sub-areas of different types, such as parking and movement slots (Chowdhary, abstract). In a first step, the parking space (lot) is surveyed, next, borders of the parking space (lot) are then input on a central server (construed as setting a zone, which naturally have ranges and a center position). Steps of the mapping include dividing the parking space (lot) into a grid of cells. A final step is the parking space (lot) is digitized and ready for real-time vehicle/object placement (Chowdhary, col 4, lines 10-16; col 7, lines 1-44). Importantly, Chowdhary uses “parking space” to refer to an entire parking lot, and uses “parking slot” to refer to a single parking spot.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention given the teachings of Dorum and Chowdhary that a parking lot information analysis device that acquires parked vehicle position information and plots parking positions into grids of a map would include set a zone having a predetermined range including the center position information of one facility included in the map information; and divide the zone into a plurality of grids. With both Dorum and Chowdhary disclosing creating parking lot maps using grid information, and with Chowdhary additionally suggesting the grids are created by setting a zone with boundaries which naturally includes ranges and central locations, and dividing the zone into said grids, one of ordinary skill in the art of implementing a parking lot information analysis device that acquires parked vehicle position information and plots parking positions into grids of a map would include set a zone having a predetermined range including the center position information of one facility included in the map information; and divide the zone into a plurality of grids in order to ensure the grid is properly positioned over the parking lot map to create an accurate depiction of the parking spaces. One would therefore be motivated to combine these teachings as in doing so would create this parking lot information analysis device.
However, Dorum and Chowdhary may not explicitly teach every aspect of
determine that a grid corresponds to the shape information of a parking lot of the facility, when a number of pieces of parking position information plotted in the grid is equal to or greater than a predetermined value.
Penna discloses a parking lot mapping system that uses data from a plurality of vehicles including a parking event and a position of each vehicle of the plurality of vehicles (Penna, abstract). The controller 22 can divide the parking lot area into a grid-like structure. The accumulation of data from the vehicles 10 in the parking lot PL will enable the controller to determine the probability of whether each grid area is a parking spot. The controller 22 is programmed to determine a parking spot probability p based on a predetermined quantity of data including the positions of a plurality of vehicles 10 in particular probabilistic spaces over time (Penna, Figure 6, [0034]; construed as a number of pieces of parking position information plotted in the grid is equal to or greater than a predetermined value).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention given the teachings of Dorum and Chowdhary with Penna that a parking lot information analysis device that acquires parked vehicle position information and plots parking positions into grids of a map would include determining that a grid corresponds to the shape information of a parking lot of the facility, when a number of pieces of parking position information plotted in the grid is equal to or greater than a predetermined value. With Dorum, Chowdhary, and Penna disclosing creating parking lot maps using grid information, and with Penna additionally suggesting once parking spots are determined based on a probability in grid locations that is established based on a number of detected parked vehicles over time which is turn is used to inform the layout of the parking lot, one of ordinary skill in the art of implementing a parking lot information analysis device that acquires parked vehicle position information and plots parking positions into grids of a map would include determining that a grid corresponds to the shape information of a parking lot of the facility, when a number of pieces of parking position information plotted in the grid is equal to or greater than a predetermined value in order to use a level of confidence that grids are part of parking spots ultimately ensuring the accuracy of parking lot map. One would therefore be motivated to combine these teachings as in doing so would create this parking lot information analysis device.
Regarding claim 2, Dorum and Chowdhary with Penna teach the parking lot information analysis device according to claim 1, wherein the processor determines an outline of a group of grids determined as the parking lot as the shape information of the parking lot of the facility as boundary information of the parking lot. More specifically, the grid cells are likely parking locations based on probe data (Dorum, abstract, [0005], [0040]) the clusters are made up of grids (Dorum, [0054]). The clusters form the contour model/boundary of the parking lot (Dorum, [0005], [0058])
Regarding claim 4, Dorum and Chowdhary with Penna teach the parking lot information analysis device according to claims 1, further the processor configured to execute the program and control the parking lot information analysis device to: store the shape information of the parking lot of the facility determined by the parking lot determination unit in the map information storage unit. More specifically, map data is updated with the determined parking lot boundary (Dorum, [0068]).
Regarding claim 5, this claim recites the method performed by the parking lot information analysis device of claim 1, therefore, the same rationale of rejection is applicable.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Dorum, Chowdhary, and Penna, and further in view of Gill et al. (US 2022/0164089 A1, citations are to Provisional Application No. 63/117,298 filed 11/23/2020, hereinafter “Gill”).
Regarding claim 3, Dorum and Chowdhary with Penna teach the parking lot information analysis device according to claim 1, including that the determined boundary can expand to maintain sufficient shape fidelity of the contour or decrease if the contour boundary only includes a few or no high likelihood parking locations (Dorum, [0065]). Adjacent parking lots having respective boundaries that overlap are identifiable (Dorum, [0067]).
However, Dorum and Chowdhary with Penna may not explicitly teach every aspect of wherein the processor identifies a grid where the number of parking position data points, previously determined to belong to the parking lot of one facility shifts from decreasing to increasing as part of a parking lot of another adjacent facility different from said facility, and determines the shape information of the parking lot of the facility as boundary information of parking lots of said facility and another adjacent facility.
Gill discloses a system for managing a fleet of vehicles by receiving vehicle position data (Gill, page 1, paragraphs 1-3). Zones can be vehicle parking regions (Gill, page 2, paragraph 1, Figure 1). Gill’s system improves on the manual creation of zones by automatically generating the zones based on the vehicle data (Gill, page 2, paragraphs 3 and 4). The vehicles that are determined to be stopped are clustered based on density data (Gill, page 4, paragraphs 1-3). Zones (construed as individual parking lots) are created for each cluster (Gill, page 5, paragraphs 1-3, Figure 3). Therefore, Gill describes determining distinct parking regions (which can be considered distinct parking areas/lots for different facilities) by clustering based on density of parked vehicles, which means a decreased density indicates a boundary for the parking areas/lots.
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention given the teachings of Dorum, Chowdhary, and Penna with Gill that a parking lot information analysis device that acquires parked vehicle position information and maps parking lots on map as well as having the ability to identify adjacent parking lots having respective boundaries that overlap would include determining the boundary between adjacent parking lots by identifying a decrease and subsequent increase of parking data points. With Dorum, Chowdhary, Penna, and Gill disclosing creating parking lot maps using parked vehicle data, with Dorum and Gill disclosing identifying boundaries between parking areas, and with Gill additionally suggesting the boundaries are identified based on decreased density of parking data, one of ordinary skill in the art of implementing a parking lot information analysis device that acquires parked vehicle position information and maps parking lots on map as well as having the ability to identify adjacent parking lots having respective boundaries that overlap would include determining the boundary between adjacent parking lots by identifying a decrease and subsequent increase of parking data points in order to create information that a parking lot could include parking areas for distinct purposes/facilities to better inform drivers. One would therefore be motivated to combine these teachings as in doing so would create this parking lot information analysis device.
Pertinent Prior Art
The prior art made of record on form PTO-892 and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
Takeuchi (US 2021/0284139 A1) – parking information is received by a plurality of vehicles. A coordinate system is divided into grids. A map of the parking lot is created.
Elie (US 2017/0197615 A1) – parking information is received by a plurality of vehicles. A region is divided into grids. A map of the parking lot is created.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PATRICK F RIEGLER whose telephone number is (571)270-3625. The examiner can normally be reached M-F 9:30am-6:00pm, ET.
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/PATRICK F RIEGLER/ Primary Examiner, Art Unit 2171
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