DETAILED ACTION
This Office Action is in response to Applicant's Application filed on 11/6/2024.
Claims 1-20 are pending for examination.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/6/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claim 1-20 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.
The claims are generally narrative and indefinite, failing to conform with current U.S. practice. They appear to be a literal translation into English from a foreign document and are replete with grammatical and idiomatic errors.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis-Step 1
Claims 1-17 are directed to A vehicle matching method (i.e., a process). Therefore, claims 1-17 are within at least one of the four statutory categories.
101 Analysis-Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for reminder of the 101 rejection. Claim 1 recites:
A vehicle matching method, performed by a server, comprising:
obtaining floating vehicle data of a target vehicle, the floating vehicle data being collected frame by frame by a positioning device at the target vehicle, and the floating vehicle data including a geographic location of the target vehicle;
determining, based on a current geographic location at a current frame moment, a candidate geographic region covering the current geographic location;
obtaining candidate vehicle sensing data of at least one candidate vehicle in the candidate geographic region, the candidate vehicle sensing data being collected frame by frame by a sensing device located in the candidate geographic region;
for each of the at least one candidate vehicle:
calculating a relative location error degree between the target vehicle and the candidate vehicle based on the floating vehicle data at the current frame moment and the candidate vehicle sensing data at the current frame moment; and
calculating a matching confidence between the target vehicle and the candidate vehicle at the current frame moment based on the relative location error degree between the target vehicle and the candidate vehicle at the current frame moment; and
selecting, from the at least one candidate vehicle, a matching candidate vehicle that successfully matches the target vehicle at the current frame moment, the relative location error degree of the matching candidate vehicle satisfying an error-degree threshold condition, and the matching confidence of the matching candidate vehicle satisfying a confidence threshold condition.
The examiner submits that the foregoing bolded limitation(s) constitute a "mental process" and/or “certain methods of organizing human activity” because under its broadest reasonable interpretation, the claim covers performance of the limitation by a user or in the human mind. For example, “determining, based on a current geographic location at a current frame moment, a candidate geographic region covering the current geographic location” in the context of this claim encompasses the user mentally determining a region. Similarly, the limitation of "calculating a relative location error degree between the target vehicle and the candidate vehicle based on the floating vehicle data at the current frame moment and the candidate vehicle sensing data at the current frame moment" in the context of this claim encompasses the user mentally calculating error. Furthermore, the limitation of “calculating a matching confidence between the target vehicle and the candidate vehicle at the current frame moment based on the relative location error degree between the target vehicle and the candidate vehicle at the current frame moment” in the context of this claim encompasses the user mentally calculating confidence. Lastly, the limitation of “selecting, from the at least one candidate vehicle, a matching candidate vehicle that successfully matches the target vehicle at the current frame moment, the relative location error degree of the matching candidate vehicle satisfying an error-degree threshold condition, and the matching confidence of the matching candidate vehicle satisfying a confidence threshold condition” in the context of this claim encompasses the user mentally selecting a vehicle. Accordingly, the claim recites at least one abstract idea.
101 Analysis-Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim as a whole, integrates the abstract into a partial application. As noted in the 2019 PEG, it must be determined whether there are any additional elements recited in the claim beyond the judicial exception(s), and whether those additional elements integrate the exception into a practical application of the exception.
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A vehicle matching method, performed by a server, comprising:
obtaining floating vehicle data of a target vehicle, the floating vehicle data being collected frame by frame by a positioning device at the target vehicle, and the floating vehicle data including a geographic location of the target vehicle;
determining, based on a current geographic location at a current frame moment, a candidate geographic region covering the current geographic location;
obtaining candidate vehicle sensing data of at least one candidate vehicle in the candidate geographic region, the candidate vehicle sensing data being collected frame by frame by a sensing device located in the candidate geographic region;
for each of the at least one candidate vehicle:
calculating a relative location error degree between the target vehicle and the candidate vehicle based on the floating vehicle data at the current frame moment and the candidate vehicle sensing data at the current frame moment; and
calculating a matching confidence between the target vehicle and the candidate vehicle at the current frame moment based on the relative location error degree between the target vehicle and the candidate vehicle at the current frame moment; and
selecting, from the at least one candidate vehicle, a matching candidate vehicle that successfully matches the target vehicle at the current frame moment, the relative location error degree of the matching candidate vehicle satisfying an error-degree threshold condition, and the matching confidence of the matching candidate vehicle satisfying a confidence threshold condition.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “obtaining floating vehicle data of a target vehicle, the floating vehicle data being collected frame by frame by a positioning device at the target vehicle, and the floating vehicle data including a geographic location of the target vehicle” and “obtaining candidate vehicle sensing data of at least one candidate vehicle in the candidate geographic region, the candidate vehicle sensing data being collected frame by frame by a sensing device located in the candidate geographic region”, the examiner submits that these limitations are mere data gathering in conjunction with a law of nature or abstract idea (MPEP § 2106.05). In particular, “obtaining floating vehicle data” and “obtaining candidate vehicle sensing data” indicate pre-solution activity such that it amounts no more than a step of gathering data for use in a claimed process.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add no thing that is nor already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2 106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis-Step 2B
Regarding Step 2B of the Revised Guidance, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional limitation of “obtaining floating vehicle data of a target vehicle, the floating vehicle data being collected frame by frame by a positioning device at the target vehicle, and the floating vehicle data including a geographic location of the target vehicle” and “obtaining candidate vehicle sensing data of at least one candidate vehicle in the candidate geographic region, the candidate vehicle sensing data being collected frame by frame by a sensing device located in the candidate geographic region”, the examiner submits that the limitation merely adds insignificant extra-solution activity to the at least one abstract idea as previously discussed.
Hence the claim is not patent eligible.
Therefore, claim(s) 1 is/are ineligible under 35 U.S.C. 101.
Regarding Claim 2, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application and narrowing limitations which is merely insignificant extra solution activity and fail to integrate the abstract idea into a practical application.
Regarding Claim 3, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application.
Regarding Claim 4, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application.
Regarding Claim 5, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application and narrowing limitations which is merely insignificant extra solution activity and fail to integrate the abstract idea into a practical application.
Regarding Claim 6, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application.
Regarding Claim 7, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application.
Regarding Claim 8, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application.
Regarding Claim 9, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application.
Regarding Claim 10, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application.
Regarding Claim 11, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application.
Regarding Claim 12, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application.
Regarding Claim 13, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application and narrowing limitations which is merely insignificant extra solution activity and fail to integrate the abstract idea into a practical application.
Regarding Claim 14, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application and narrowing limitations which is merely insignificant extra solution activity and fail to integrate the abstract idea into a practical application.
Regarding Claim 15, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application and narrowing limitations which is merely insignificant extra solution activity and fail to integrate the abstract idea into a practical application.
Regarding Claim 16, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application and narrowing limitations which is merely insignificant extra solution activity and fail to integrate the abstract idea into a practical application.
Regarding Claim 17, the claim recites limitations which further narrowing the abstract idea and fail to integrate the abstract idea into a practical application and narrowing limitations which is merely insignificant extra solution activity and fail to integrate the abstract idea into a practical application.
As per claim 18, it recites A computer device having limitations similar to those of claim 1 and therefore is rejected on the same basis. Regarding the additional limitations of “one or more memories storing computer-readable instructions; and one or more processors configured to execute the computer-readable instructions”, the examiner submits that these limitations are mere instructions to apply the above noted abstract idea by merely using a computer to perform the process (MPEP § 2106.05). In particular, one or more memories recited at a high-level of generality (i.e., as memory performing a generic computer function of storing instruction) such that it amounts no more than mere instructions to apply the exception using a generic computer component. One or more processors recited at a high-level of generality (i.e., as processor performing a generic computer function of executing instruction) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
As per claim 19, it recites A computer device having limitations similar to those of claim 2 and therefore is rejected on the same basis.
As per claim 20, it recites A non-transitory computer-readable storage medium having limitations similar to those of claim 1 and therefore is rejected on the same basis.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 4-8, 11-12, 18-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Takla (US20210280064A1).
Regarding claim 1, Takla teaches A vehicle matching method, performed by a server, comprising:
obtaining floating vehicle data of a target vehicle, the floating vehicle data being collected frame by frame by a positioning device at the target vehicle, and the floating vehicle data including a geographic location of the target vehicle(Takla: Para 11 “locations of vehicles and pedestrians might be reported by different sources, such as vehicle on-board diagnostic devices (OBDs, also referred to at telematics devices), roadside cameras, global positioning systems (GPS), and the like”);
determining, based on a current geographic location at a current frame moment, a candidate geographic region covering the current geographic location(Takla: Para 42 “FIG. 4 is an illustration of a data cluster showing variations in location data. In the example of FIG. 4, assume location data, which is associated with vehicle 110-1, from three different sources is provided. Primary location data (CL1) 402 may be provided, for example, from an OBD 112 (not shown) for vehicle 110-1. Redundant data (CL2) 404 may be provided, for example, from a triangulation of a mobile device 120 of a passenger in vehicle 110-1. Redundant data (CL3) 406 may be provided, for example, from a GPS tracking signal for another mobile device 120 in vehicle 110-1. As further shown in FIG. 4, assume location data, which is associated with vehicle 110-2, from another source is provided. Non-redundant data (CL3) 408 may be provided, for example, from a GPS tracking signal for another mobile device 120 in vehicle 110-2”);
obtaining candidate vehicle sensing data of at least one candidate vehicle in the candidate geographic region, the candidate vehicle sensing data being collected frame by frame by a sensing device located in the candidate geographic region(Takla: Para 54 “Returning to FIG. 6, RAN 130 may report CL2 data 604 which may include, for example, triangulation position data for a mobile communication device 120 (e.g., mobile communication device 120-2, not shown) of a passenger in vehicle 110-1. Mobile communication device 120 may report CL3 data 606 which may include, for example, GPS location information for mobile device 120-1 in vehicle 110-1. Camera 122 may report CL3 data 608 which may include, for example, images or video of an area where vehicles 110-1 and 110-2 (e.g., vehicles including OBDs 112-1 and 112-2) are located”);
for each of the at least one candidate vehicle:
calculating a relative location error degree between the target vehicle and the candidate vehicle based on the floating vehicle data at the current frame moment and the candidate vehicle sensing data at the current frame moment(Takla: Para 62 “V2X communications handler 610 may search from the center of the RTK vehicle for the presence of other reported vehicles within a maximum error range. The maximum error range may be calculated as a function of the positioning error of one vehicle (e.g., centimeters for the RTK vehicle) plus the positioning error of the second vehicle (e.g., one or more meters for the non-RTK vehicle) and any reported vehicle dimensions”); and
calculating a matching confidence between the target vehicle and the candidate vehicle at the current frame moment based on the relative location error degree between the target vehicle and the candidate vehicle at the current frame moment(Takla: Para 63 “If another vehicle is within a maximum error range (block 915—Yes), it may be determined if the vehicles have matching trajectories (block 920). For example, V2X communications handler 610 may compare recent location data from each of the RTK vehicle and the non-RTK vehicle to determine if they have the same trajectory (i.e., collinear trajectories)”; Para ); and
selecting, from the at least one candidate vehicle, a matching candidate vehicle that successfully matches the target vehicle at the current frame moment, the relative location error degree of the matching candidate vehicle satisfying an error-degree threshold condition, and the matching confidence of the matching candidate vehicle satisfying a confidence threshold condition(Takla: Para 66 “If there is corroborating data available (block 925—Yes), the other vehicle information is marked as a duplicative and not shared (block 935). For example, V2X communications handler 610 may confirm a trajectory with at least one other piece of corroborating data to verify that the RTK vehicle and the non-RTK vehicle are the same. Thus, communications handler 610 may suppress (or not share) message with the redundant, less-accurate non-RTK vehicle data”).
Regarding claim 4, Takla teaches The method according to claim 1, further comprising:
in response to determining that the at least one candidate vehicle is not in the vehicle-following mode at the previous frame moment, performing the operation of calculating the relative location error degree and the candidate vehicle sensing data at the current frame moment for each of the at least one candidate vehicle(Takla: Para 62 “If CL1 data is available (block 905—Yes), process block 815 may include confirming a location on an HD map (block 910), and determining if other vehicles are within a maximum error range (block 915). For example, for every RTK vehicle data set, V2X communications handler 610 may confirm the RTK vehicle's location on the HD-MAP (e.g., from map system 170) to ensure that the vehicle is in a specific lane/road and direction. V2X communications handler 610 may search from the center of the RTK vehicle for the presence of other reported vehicles within a maximum error range. The maximum error range may be calculated as a function of the positioning error of one vehicle (e.g., centimeters for the RTK vehicle) plus the positioning error of the second vehicle (e.g., one or more meters for the non-RTK vehicle) and any reported vehicle dimensions”);
wherein a vehicle being in the vehicle-following mode refers to that there is a matching vehicle that successfully matches the vehicle, a relative location error degree between the vehicle and the matching vehicle satisfies a preset vehicle-following mode error-degree threshold condition of the vehicle-following mode, and a matching confidence between the vehicle and the matching vehicle satisfies a preset vehicle-following mode confidence threshold condition(Takla: Para 63 “If another vehicle is within a maximum error range (block 915—Yes), it may be determined if the vehicles have matching trajectories (block 920). For example, V2X communications handler 610 may compare recent location data from each of the RTK vehicle and the non-RTK vehicle to determine if they have the same trajectory (i.e., collinear trajectories)”; Para 64 “If the vehicles have matching trajectories (block 920—Yes), it may be determined if there is corroborating data available to confirm duplicate vehicles (block 925). For example, V2X communications handler 610 may determine if other telematics data from the RTK vehicle and the non-RTK vehicle can be matched. For example, speed, size, color, or other data reported for each vehicle data point may be matched”).
Regarding claim 5, Takla teaches The method according to claim 4, further comprising:
traversing candidate vehicle sensing data of the at least one candidate vehicle at the previous frame moment, to determine if the candidate vehicle sensing data of the at least one candidate vehicle at the previous frame moment includes a vehicle-following mode identifier(Takla: Para 64 “If the vehicles have matching trajectories (block 920—Yes), it may be determined if there is corroborating data available to confirm duplicate vehicles (block 925)”; Para 65 “If no corroborating data is available (block 925—No), extended observation may be performed (block 930) before returning to process block 925. For example, V2X communications handler 610 may extend observation for a new time period ΔT (where ΔT is a small enough time to see if two vehicles are on a collision course or, in fact, the same vehicle)”); and
in response to failing to read the vehicle-following mode identifier after the traversing ends, determining that the at least one candidate vehicle is not in the vehicle-following mode at the previous frame moment(Takla: Para 65 “If no corroborating data is available (block 925—No), extended observation may be performed (block 930) before returning to process block 925. For example, V2X communications handler 610 may extend observation for a new time period ΔT (where ΔT is a small enough time to see if two vehicles are on a collision course or, in fact, the same vehicle)”).
Regarding claim 6, Takla teaches The method according to claim 4, further comprising:
in response to determining that one candidate vehicle of the at least one candidate vehicle is in the vehicle-following mode at the previous frame moment, determining a physical distance between the one candidate vehicle and the target vehicle based on the floating vehicle data at the current frame moment and candidate vehicle sensing data of the one candidate vehicle at the current frame moment(Takla: Para 71 “Process block 825/835 may also include determining if other vehicles are within a maximum error range (block 1015). For example, V2X communications handler 610 may search from the center of the CL2 or CL3 vehicle for the presence of other reported vehicles within a maximum error range. The maximum error range may be calculated as a function of the positioning error of one vehicle (e.g., up to one meter for the CL2 vehicle) plus the positioning error of the second vehicle (e.g., more than one meter for a CL3 vehicle) and any reported vehicle dimensions”; Para 72 “If another vehicle is within a maximum error range (block 1015—Yes), it may be determined if the vehicles have matching trajectories (block 1020). For example, V2X communications handler 610 may compare recent location data from each of the CL2 vehicle and a CL3 vehicle (e.g., that is within the maximum error range) to determine if they have the same trajectory”); and
in response to the physical distance being not greater than a preset distance threshold, determining that the one candidate vehicle successfully matches the target vehicle, and maintaining the one candidate vehicle in the vehicle-following mode at the current frame moment(Takla: Para 72 “If another vehicle is within a maximum error range (block 1015—Yes), it may be determined if the vehicles have matching trajectories (block 1020). For example, V2X communications handler 610 may compare recent location data from each of the CL2 vehicle and a CL3 vehicle (e.g., that is within the maximum error range) to determine if they have the same trajectory”).
Regarding claim 7, Takla teaches The method according to claim 6, further comprising:
in response to the physical distance being greater than the preset distance threshold, performing the operation of calculating the relative location error degree and the candidate vehicle sensing data at the current frame moment for each of the at least one candidate vehicle(Takla: Fig. 9 Element 915 and Fig. 10 1015; Para 71 “Process block 825/835 may also include determining if other vehicles are within a maximum error range (block 1015). For example, V2X communications handler 610 may search from the center of the CL2 or CL3 vehicle for the presence of other reported vehicles within a maximum error range. The maximum error range may be calculated as a function of the positioning error of one vehicle (e.g., up to one meter for the CL2 vehicle) plus the positioning error of the second vehicle (e.g., more than one meter for a CL3 vehicle) and any reported vehicle dimensions”; i.e. the figure indicated the determining if other vehicles are within a maximum error range (block 915) continues to block 820 including determining if other vehicles are within a maximum error range (block 1015)).
Regarding claim 8, Takla teaches The method according to claim 1, further comprising:
in response to the relative location error degree between the matching candidate vehicle and the target vehicle satisfying a preset vehicle-following mode error-degree threshold condition and the matching confidence between the matching candidate vehicle and the target vehicle satisfying a preset vehicle-following mode confidence threshold condition at the current frame moment, recording that the matching candidate vehicle is in a vehicle-following mode(Takla: Para 72 “If another vehicle is within a maximum error range (block 1015—Yes), it may be determined if the vehicles have matching trajectories (block 1020). For example, V2X communications handler 610 may compare recent location data from each of the CL2 vehicle and a CL3 vehicle (e.g., that is within the maximum error range) to determine if they have the same trajectory”); and
adding a vehicle-following mode identifier to candidate vehicle sensing data of the matching candidate vehicle at the current frame moment(Takla: Para 73 “If the vehicles have matching trajectories (block 1020—Yes), it may be determined if there is corroborating data available to confirm duplicate vehicles (block 1025). For example, V2X communications handler 610 may determine if other telematics data from the CL2 vehicle and the CL3 vehicle (or two CL3 vehicles) can be matched. For example, speed, size, color, or other data reported for each vehicle data point may be matched”);
wherein a vehicle being in the vehicle-following mode refers to that there is a matching vehicle that successfully matches the vehicle(Takla: Para 7 “The communications management device select high vulnerability trajectories based on the calculated trajectories and identifies when the telematics data from different sources, of the multiple sources, corresponds to a same vehicle”), a relative location error degree between the vehicle and the matching vehicle satisfies a preset vehicle-following mode error-degree threshold condition of the vehicle-following mode(Takla: Para 72 “If another vehicle is within a maximum error range (block 1015—Yes), it may be determined if the vehicles have matching trajectories (block 1020)”), and a matching confidence between the vehicle and the matching vehicle satisfies a preset vehicle-following mode confidence threshold condition(Takla: Para 73 “If the vehicles have matching trajectories (block 1020—Yes), it may be determined if there is corroborating data available to confirm duplicate vehicles (block 1025).”).
Regarding claim 11, Takla teaches The method according to claim 1, further comprising:
determining, for one candidate vehicle of the at least one candidate vehicle, that the one candidate vehicle does not match the target vehicle in response to a relative location error degree between the one candidate vehicle and the target vehicle being greater than a preset error-degree threshold(Takla: Para 67 “If no CL1 data is available (block 905—No), if no other vehicle is within a maximum error range (block 915—No), if the vehicles do not have matching trajectories (block 920—No), or after the other vehicle information is marked as duplicative and not shared (block 935), process block 815 may proceed to process block 820. For example, communications handler 610 may proceed to report any CL1 data to collision avoidance system 620”).
Regarding claim 12, Takla teaches The method according to claim 1, further comprising:
determining, for one candidate vehicle of the at least one candidate vehicle, that the one candidate vehicle does not match the target vehicle in response to a matching confidence between the one candidate vehicle and the target vehicle being less than a preset confidence threshold(Takla: Para 67 “If no CL1 data is available (block 905—No), if no other vehicle is within a maximum error range (block 915—No), if the vehicles do not have matching trajectories (block 920—No), or after the other vehicle information is marked as duplicative and not shared (block 935), process block 815 may proceed to process block 820. For example, communications handler 610 may proceed to report any CL1 data to collision avoidance system 620”).
As per claim 18, it recites A computer device having limitations similar to those of claim 1 and therefore is rejected on the same basis. Takla further teaches one or more memories storing computer-readable instructions; and one or more processors configured to execute the computer-readable instructions(Takla: Para 28 “OBD device 112, mobile communication device 120, camera 122, base station 135, MEC device 145, map system 170, and/or VCP 180 may each include, or be implemented on, one or more devices 200. As shown in FIG. 2, device 200 may include a bus 210, a processor 220, a memory 230, an input device 240, an output device 250, and a communication interface 260”).
As per claim 19, it recites A computer device having limitations similar to those of claim 2 and therefore is rejected on the same basis.
As per claim 20, it recites A non-transitory computer-readable storage medium having limitations similar to those of claim 1 and therefore is rejected on the same basis. . Takla further teaches A non-transitory computer-readable storage medium(Takla: Para 28 “OBD device 112, mobile communication device 120, camera 122, base station 135, MEC device 145, map system 170, and/or VCP 180 may each include, or be implemented on, one or more devices 200. As shown in FIG. 2, device 200 may include a bus 210, a processor 220, a memory 230, an input device 240, an output device 250, and a communication interface 260”).
Allowable Subject Matter
Claim 2-3, 9-10 , 13-17 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action. In particular, the limitations of “determining, from a preset geographic-grid set, a target geographic grid in which the current geographic location is located, the geographic-grid set including a plurality of geographic grids each arranged with a sensing device; and determining, based on at least the target geographic grid, the candidate geographic region covering the target geographic grid; and obtaining the candidate vehicle sensing data of the at least one candidate vehicle in the candidate geographic region includes: obtaining, for each geographic grid in the candidate geographic region, the candidate vehicle sensing data of the at least one candidate vehicle that is collected by the sensing device in the geographic grid” in claim 2, “calculating a weight value of the candidate vehicle at the current frame moment based on the relative location error degree between the target vehicle and the candidate vehicle at the current frame moment, the weight value being negatively correlated with the relative location error degree; and calculating, based on the weight value at the current frame moment, the matching confidence between the target vehicle and the candidate vehicle at the current frame moment, the matching confidence being positively correlated with the weight value” in claim 9, “calculating multi-dimensional feature error degrees based on the multi-dimensional target vehicle feature data at the current frame moment and the multi-dimensional candidate vehicle feature data of the candidate vehicle at the current frame moment; and calculating the relative location error degree between the target vehicle and the candidate vehicle based on the multi-dimensional feature error degrees” claim 13 were not uncovered in the prior art teachings.
Claims 3, 10, 14-17 would be allowable based on the dependence on claims 2, 9, 13 therefor inheriting the allowable subject matter disclosed in claims 2, 9, 13.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Uchiyama (US20220343757A1) disclosed improvement of a recognition level, on the basis of information of communication between mobile devices such as vehicles or communication between a vehicle and an infrastructure system.
Itoh (US20220034999A1) disclosed an abnormality detection method of an infrastructure sensor apparatus configured to detect a mobile body that passes within a sensing range, the abnormality detection method including: calculating mobile body information at least including positional information and moving speed information on the mobile body based on information on the mobile body detected by the infrastructure sensor apparatus; calculating probe data at least including positional information and moving speed information on the mobile body based on self positional information of the mobile body received using a radio communication function included in the mobile body; and performing abnormality determination processing in which it is determined that there is an abnormality in the infrastructure sensor apparatus when the mobile body information does not match the probe data.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WENYUAN YANG whose telephone number is (571)272-5455. The examiner can normally be reached Monday - Thursday 9:00AM-5:00PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hitesh Patel can be reached at (571) 270-5442. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/W.Y./Examiner, Art Unit 3667
/Hitesh Patel/Supervisory Patent Examiner, Art Unit 3667
3/26/26
Prosecution Insights