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 .
DETAILED ACTION
This action is in response to the claims filed 1/17/2025. Claims 1-4 are pending for examination.
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 1-4 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim 1 recites the abstract idea of “comparing data based on past insurance claim outcomes and assigning fault ratio”, which is grouped under “Certain Methods of Organizing Human Activity” such as fundamental economic principles or practices (mitigating risk; insurance) (MPEP 2016.04(a)). Specifically, claim 1 recites “including at least one… and at least one…communicate data over one or more types of…”, “wherein the …is operatively couples to the at least one …wherein the at least one …stores instructions that…”, “obtaining … information from a … via the one or more types of … using the …, wherein the …information is recorded using a detected accident”, “identify one or more objects outside the … at a location of the detected accident using the …information”, “determining a path projection for the … and for the one or more identified objects using the …information”, “generating incident data including the path projection for the … and for the one or more identified objects”, “compare the incident data to a model trained on past insurance claim outcomes” and “assign a fault ratio for the accident to the …. and/or the one or more objects based on the comparison”. Claims 2-4 are dependent on claim 1 and include all the limitations of claim 1. Therefore, claims 2-4 recite the same abstract idea of “comparing data based on past insurance claim outcomes and assigning fault ratio”. The limitations recited in the depending claims (For example, the processing and determining steps) are further details of the abstract idea and not significantly more. The concept described in claims 1-4 are not meaningfully different than those concepts found by the courts to be abstract ideas. As such, the description in claims 1-4 is an abstract idea.
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A (MPEP 2106.04II), the additional elements of claim 1 such as “a communication interface including at least one transmitter and at least one receiver”, “networks”, “memory device”, “processing circuit” and “for the vehicle” represent the use of a computer as a tool to perform an abstract idea and/or does no more than generally link the abstract idea to a particular technological environment or field of use. With respect to obtaining “vehicle sensor (information)” from a “vehicle”, identifying objects “outside the vehicle” and assigning ratio to the “vehicle”, the claim lacks detail regarding what “obtaining”, “identifying” and “assigning” comprise (MPEP 2106.05(f)(1)) and do not provide a practical application. With respect to “machine learning” recited in claim 2, the claim lack detail regarding what “training” comprise (MPEP 2106.05(f)(1)). With respect to “identified…. vehicles” recited in claims 3, the claim lack detail regarding how the vehicles are identified (MPEP 2106.05(f)(1)). With respect to “of the one or more other vehicles” recited in claims 3 and 4, the limitation does no more than generally link the abstract idea to a particular technological environment or field of use. Therefore, as Applicant has neither placed a restriction on how the actions are performed nor describe how the functions are accomplished the limitations do not integrate the abstract idea into a practical application as they are no more than “apply it” (MPEP 2106.05(f)(1)).
When analyzed under step 2B (MPEP 2106.04II), because the additional elements do no more than represent the use of a computer as a tool to perform an abstract idea and/or does no more than generally link the abstract idea to a particular field of use, they do not provide an improvement to computer functionality, or an improvement to another technology or technical field and, therefore, do not amount to significantly more than the judicial exception itself (MPEP 2106.05(I)(A)(f)&(h)).
Hence, claims 1-4 are not patent eligible.
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.
Claims 1-2 and 4 are rejected under 35 U.S.C. 103 as being unpatentable over Gong et al. (US 2017/0004662 A1) in view of Fields et al. (US 9,868,394 B1) and Anthony (US 2008/0077451 A1).
As per Claim 1
Gong (‘662) discloses
a communication interface including at least one transmitter and at least one receiver, see at least paragraph 0085 (communication modules and can include transmitters and/or receivers configured to transmit and/or receive data), paragraph 0006 (interface)
wherein the communication interface is configured to communicate data over one or more types of networks, paragraph 0073 (wireless connection; WiFi, Bluetooth, or mobile or cellular phone networks)
a memory device, see at least paragraph 0004 (the device may comprise a memory)
a processing circuit, wherein the processing circuit is operatively coupled to the at least one memory device, see at least paragraph 0080 (processing unit may comprise instructions), paragraph 0160 (processing unit can be operatively coupled to a non0transitory computer readable medium…include one or more memory units)
wherein the at least one memory device stores instructions that, when executed by the at least one processing circuit, configures the computing system to, see at least paragraph 0080 (processing unit may comprise instructions), paragraph 0160 (processing unit can be operatively coupled to a non0transitory computer readable medium…include one or more memory units)
obtain vehicle sensor information from a vehicle via the one or more types of networks using the communication interface, see at least paragraph 0002 (vehicles
may be equipped with sensor for collecting data; sensors for detecting parameters such as speed, altitude and location of a vehicle), paragraph 0159 (sensing module can be operatively coupled toa transmission module e.g. a Wi-Fi image transmission module configured to directly transmit sensing data to a suitable external device or system; transmit image captured by a camera of the sensing module to a remote terminal)
wherein the vehicle sensor information is recorded during a detected accident, see at least paragraph 0041 (uploading of the vehicle operation data…may be performed when the vehicle operation data recorder is alerted that one or more accident conditions are detected) and claim 13 of Gong (accident conditions are selected from…data from a vision sensor of a vehicle indicating poor visibility)
Gong (‘662) discloses identifying environment outside of the vehicle using the vehicle sensor information, see at least paragraph 0037 (pictures taken by the camera of a surrounding environment of the vehicle) and paragraph 0129 (vehicle may apply to and used for any movable object….such as in air… aircraft….on ground e.g. motor vehicle such as car, truck, bus, van, motorcycle), but fails to explicitly disclose identify one or more objects outside the vehicle at a location of the detected accident, determine a path projection for the vehicle and for the one or more identified objects using the vehicle sensor information and generate incident data including the path projection for the vehicle and for the one or more identified objects and assign a fault ratio for the accident to the vehicle and/or the one or more objects based on comparison. Fields (‘394) teaches identify one or more objects outside the vehicle at a location of the detected accident, determine a path projection for the vehicle and for the one or more identified objects using the vehicle sensor information and generate incident data including the path projection for the vehicle and for the one or more identified objects and assign a fault ratio for the accident to the vehicle and/or the one or more objects based on comparison, see at least column 35, lines 47-66 (reconstruct the movements or path of the vehicles based upon the received sensor data; movements or paths of other vehicles and/or other aspects of the vehicle operating environment may be restricted for a period including the anomalous condition), column 36, lines 1-9 (comparing the reconstructed path of the vehicle with paths of the other vehicles in the vehicle operating environment) and column 32, line 1-6 (accidents may include a collision between vehicles…collision between a vehicle and animals or a collision between a vehicle and another object) and column 28, lines 54-67 (compare…to determine if the vehicle or another vehicle was a cause of the vehicle accident ….updating…an insurance policy premium or discount based upon which vehicle caused the vehicle accident to facilitate not penalizing not-at-fault drivers). Both Gong and Fields are directed to identifying environment outside of a vehicle. Therefore, the Examiner asserts that it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gong’s invention to include identify one or more objects outside the vehicle at a location of the detected accident, determine a path projection for the vehicle and for the one or more identified objects using the vehicle sensor information and generate incident data including the path projection for the vehicle and for the one or more identified objects and assign a fault ratio for the accident to the vehicle and/or the one or more objects based on comparison. One would have been motivated to do so for the benefit of reducing risk.
Gong (‘662) fails to explicitly disclose compare the incident data to a model trained on past insurance claim outcomes. Anthony (‘451) teaches compare incident data to a model trained on past insurance claim outcomes, see at least paragraph 0047 (incident occurred at a location extract from text in a claims file; data can then be compared…databases), paragraph 0050 (compared to data obtained…determine what the claimed damage was likely sustained due to storm), paragraph 0041 (predictive models…trained on prior data and outcomes known to the insurance company; predict model used to predict the ultimate severity of an insurance claim….trained on a collection of data known about prior insurance claims and…cost), paragraph 0042 (predictive model outputs a predicted total cost). Both Gong and Fields are directed to identifying data related to vehicle accident. Therefore, the Examiner asserts that it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gong’s invention to include compare the incident data to a model trained on past insurance claim outcomes. One would have been motivated to do so for the benefit of reducing risk.
As per Claim 2
Gong (‘662) disclose process the incident data and determining cost for the detected accident, see at least paragraph 0125 (if a user is determined to be at fault e.g. vehicle behavior was a result of user-entered command, the user may be personally held accountable for paying for the costs; if a third-party or environment conditions are determined to be at fault, such as…hijacking incident, the user’s insurance…may partially or completely cover the costs of the damage), but fails to explicitly disclose process the data using a machine learning model. Fields (‘394) teaches process data using a machine learning model, see at least column 65, lines 37-41 (inputting …data into a trained machine learning program). Both Gong and Fields are directed to identifying environment outside of a vehicle. Therefore, the Examiner asserts that it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gong’s invention to include process the data using a machine learning model. One would have been motivated to do so for the benefit of increasing accuracy.
Gong (‘662) fails to explicitly disclose wherein cost estimation model is trained using past insurance claims and determine a cost estimation. Anthony (‘451) teaches wherein cost estimation model is trained using past insurance claims and determine a cost estimation, see at least paragraph 0047 (incident occurred at a location extract from text in a claims file; data can then be compared…databases), paragraph 0050 (compared to data obtained…determine what the claimed damage was likely sustained due to storm), paragraph 0041 (predictive models…trained on prior data and outcomes known to the insurance company; predict model used to predict the ultimate severity of an insurance claim….trained on a collection of data known about prior insurance claims and…cost), paragraph 0042 (predictive model outputs a predicted total cost). Both Gong and Fields are directed to identifying data related to vehicle accident. Therefore, the Examiner asserts that it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gong’s invention to include wherein cost estimation model is trained using past insurance claims and determine a cost estimation. One would have been motivated to do so for the benefit of reducing risk.
As per Claim 4
Gong (‘662) fails to explicitly disclose determine an assigned cost to the one or more drivers of the one or more other vehicles wherein the assigned cost is determined using the cost estimation for the detected accident and the fault ratio assigned to the one or more other vehicles. Fields (‘394) teaches determine an assigned cost to the one or more drivers of the one or more other vehicles wherein the assigned cost is determined using the cost estimation for the detected accident and the fault ratio assigned to the one or more other vehicles, see at least column 37, lines 51-57 (data may be analyzed to determine whether the vehicle was operated in an aggressive manner preceding the hard braking event which may be associated with a heightened risk of a vehicle accident; such determination may be used to assign fault for the accident and/or adjust an insurance policy) and column 32, line 1-6 (accidents may include a collision between vehicles…collision between a vehicle) and column 28, lines 54-67 (compare…to determine if the vehicle or another vehicle was a cause of the vehicle accident ….updating…an insurance policy premium or discount based upon which vehicle caused the vehicle accident to facilitate not penalizing not-at-fault drivers). Both Gong and Fields are directed to identifying environment outside of a vehicle. Therefore, the Examiner asserts that it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gong’s invention to include determine an assigned cost to the one or more drivers of the one or more other vehicles wherein the assigned cost is determined using the cost estimation for the detected accident and the fault ratio assigned to the one or more other vehicles. One would have been motivated to do so for the benefit of allowing cost to be assigned to driver at fault.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Gong et al. (US 2017/0004662 A1) in view of Fields et al. (US 9,868,394 B1) and Anthony (US 2008/0077451 A1), as applied to claim 1 above, and further in view of Kim et al. US 2017/0206785 A1.
As per Claim 3
Gong (‘662) fails to explicitly disclose when the one or more identified objects includes one or more other vehicles, process the incident data using license plate information for the one or more other vehicles and determine an identity of one or more drivers of the one or more other vehicles using the license plate information. Fields (‘394) teaches when the one or more identified objects includes one or more other vehicles, process the incident data using license plate information for the one or more other vehicles and determine an identity of one or more drivers of the one or more other vehicles using the license plate information, see at least column 32, line 1-6 (accidents may include a collision between vehicles…collision between a vehicle and animals or a collision between a vehicle and another object), column 58, lines 11-30 (identify a target vehicle from among one or more vehicles within the operating environment of the vehicle; target vehicle may be identified….using an image of a license plate), column 61, lines 32-44 (a vehicle tag or license plate may be captured via a camera communicatively connected to the mobile computing device or on-board computer which may be processed to identify the vehicle), column 42, lines 28-50 (determine the identity of the driver of the vehicle; the identity may be first determined by a mobile computing device or on-board computer; determine the driver of the vehicle by…..cameras). Both Gong and Fields are directed to identifying environment outside of a vehicle. Therefore, the Examiner asserts that it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gong’s invention to include when the one or more identified objects includes one or more other vehicles, process the incident data using license plate information for the one or more other vehicles and determine an identity of one or more drivers of the one or more other vehicles using the license plate information. One would have been motivated to do so for the benefit of allowing driver of vehicle to be identified more easily.
Gong (‘662) fails to explicitly disclose process data using an identification model that detects license plate information. Kim (‘785) teaches process data using an identification model that detects license plate information, see at least paragraph 0039 (license plate numbers may also be detected using a machine learning model that is trained from many training plates). Both Gong and Kim are directed to processing data related to vehicle. Therefore, the Examiner asserts that it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Gong’s invention to include when the one or more identified objects includes process data using an identification model that detects license plate information. One would have been motivated to do so for the benefit of speeding up identifying process.
Related But Not Relied Upon
Relevant prior art cited but not applied: Dahl et al. (US 10,832,593 B1), directed to determining risk based on data received from vehicle sensors.
Conclusion
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/CHIA-YI LIU/Primary Examiner, Art Unit 3692