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
This Office Action is in response to the application filed on 12/22/2025. Claims 1-6, 8-13, 15-18 and 20 are presently pending and are presented for examination. Claims 1, 5, 8, 9, 10, 16, and 17 were amended. Claims 7, 14, and 19 were cancelled.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/22/2025 has been entered.
Reply to Remarks
Applicant’s arguments, see Pages 7-8 of the Applicant's Remarks, filed 12/22/2025, with respect to the rejection(s) of claim(s) 1-6, 8-13, 15-18 and 20 under §101 have been fully considered and are not persuasive. Applicant argues that the claims are not directed to an abstract idea. Examiner respectfully disagrees.
The independent claims continue to lack any form of vehicle control after the comparison steps. Further, the data alignment can be done in the mind or with pen or paper. Further, automating a manual activity is not sufficient to avoid a 101 rejection, see MPEP 2144.04 for more details. While, the Applicant argues that users rarely look at driving data or that doing so would be less safe, these arguments nevertheless fail to prove that a driver could not examine the data in real-time and make subsequent judgements regarding his/her performance relative to that of other drivers. The insignificant extra-solution activity of displaying information, such as a change in a driver’s driving pattern relative to other drivers, does not overcome the 101 rejections presented herein. Therefore, the 101 rejections are maintained.
Applicant’s arguments, see Pages 8-9 of the Applicant's Remarks, filed 12/22/2025, with respect to the rejection(s) of claim(s) 1-6, 8-13, 15-18 and 20 under §103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Kumar, Grandy, Park, and Ahn.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6, 8-13, 15-18, and 20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
As per claim 1
Step 1: The claim is directed to a process as it recites (a computer implemented method).
Step 2A Prong 1: The claim is directed to an abstract idea of a mental process. The claim recites:
A computer implemented method comprising:
receiving telematics data generated by a plurality of telematics devices disposed within a vehicle while the vehicle is being operated by a specific individual, wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices;
processing the telematics data in substantially real-time during operation of the vehicle to determine one or more driving attributes associated with the specific individual based on the telematics data, wherein one or more of the driving attributes are determined at least in part by:
aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile;
comparing the one or more driving attributes associated with the specific individual with one or more driving attributes associated with one or more connected users, the one or more driving attributes associated with one or more connected users received from one or more databases;
determining one or more trends of the one or more driving attributes associated with the specific individual;
generating data to cause a user interface to be generated presenting a result of the comparing; and
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed.
These limitations as drafted are simple processes that under their broadest reasonable interpretations cover the performance of these limitations in the mind or by hand or with pen and paper as these steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The nominal recitation of the computer, and its unrecited processor, does not take the limitation out of the mental process grouping. Thus, the claim recites a mental process which is an abstract idea.
Step 2A Prong 2: Judicial exception is not integrated into a practical application. The claim
recites the additional elements of:
A computer implemented method comprising:
receiving telematics data generated by a plurality of telematics devices disposed within a vehicle while the vehicle is being operated by a specific individual, wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices;
processing the telematics data in substantially real-time during operation of the vehicle to determine one or more driving attributes associated with the specific individual based on the telematics data, wherein one or more of the driving attributes are determined at least in part by:
aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile;
comparing the one or more driving attributes associated with the specific individual with one or more driving attributes associated with one or more connected users, the one or more driving attributes associated with one or more connected users received from one or more databases;
determining one or more trends of the one or more driving attributes associated with the specific individual;
generating data to cause a user interface to be generated presenting a result of the comparing; and
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed.
The recited computer is recited at a high level of generality and merely apply the exception using generic computer components to automate the abstract idea. Further, the instruction to receive telematics data is recited at a high level of generality (i.e., as a general means of receiving telematics data), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Further, the instruction for presenting a result of the comparing is also recited at a high level of generality (i.e., as a general means of presenting a result of the comparing, and causing the user interface to present a notification), and are similar to displaying information, which is a form of insignificant extra-solution activity. Further, the additional elements are applying the abstract ideas in a vehicle environment. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: The claim does not include additional elements that are sufficient to amount to
significantly more than the judicial exception. As discussed above with respect to Step 2A Prong
2, the additional elements amount to no more than mere instructions to apply the exception in a vehicular environment using a generic computer. Determining a difference between the observed driver and vehicle behavior and the behavior of similar drivers and their vehicles is well-understood, routine and conventional in the art, as indicated in the following rejections under 103. For these reasons, claim 1 is not patent eligible under 35 U.S.C. § 101.
As per claims 2-6, and 8-9
These method claims further define the abstract ideas of the mental processes illustrated in claim 1, they do not recite any additional elements or other limitations that transform the determinations of what data is used to make the comparison between drivers and how those comparisons are made, and these elements are well-understood, routine and conventional in the art, as indicated in the following rejections under 103.
As per claim 10
Step 1: The claim is directed to an apparatus as it recites (a system comprising).
Step 2A Prong 1: The claim is directed to an abstract idea of a mental process. The claim recites:
A system comprising:
at least one processor configured to:
receive telematics data generated by a plurality of telematics devices disposed within a vehicle while the vehicle is being operated by a specific individual, wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices;
process the telematics data in substantially real-time during operation of the vehicle to determine one or more driving attributes associated with the specific individual based on the telematics data, wherein one or more of the driving attributes are determined at least in part by:
aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile;
compare the one or more driving attributes associated with the specific individual to one or more driving attributes associated with one or more connected users, the one or more driving attributes associated with one or more connected users received from one or more databases;
determine one or more trends of the one or more driving attributes associated with the specific individual;
cause a user interface to be generated that presents a result of the comparison; and
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed.
These limitations as drafted are simple processes that under their broadest reasonable interpretations cover the performance of these limitations in the mind or by hand or with pen and paper as these steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The nominal recitation of the processor does not take the limitation out of the mental process grouping. Thus, the claim recites a mental process which is an abstract idea.
Step 2A Prong 2: Judicial exception is not integrated into a practical application. The claim
recites the additional elements of:
A system comprising:
at least one processor configured to:
receive telematics data generated by a plurality of telematics devices disposed within a vehicle while the vehicle is being operated by a specific individual, wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices;
process the telematics data in substantially real-time during operation of the vehicle to determine one or more driving attributes associated with the specific individual based on the telematics data, wherein one or more of the driving attributes are determined at least in part by:
aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile;
compare the one or more driving attributes associated with the specific individual to one or more driving attributes associated with one or more connected users, the one or more driving attributes associated with one or more connected users received from one or more databases;
determine one or more trends of the one or more driving attributes associated with the specific individual;
cause a user interface to be generated that presents a result of the comparison; and
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed.
The recited processor is recited at a high level of generality and merely apply the exception using generic computer components to automate the abstract idea. Further, the instruction to receive telematics data is recited at a high level of generality (i.e., as a general means to receive telematics data), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Further, the instruction to present a result of the comparison is also recited at a high level of generality (i.e., as a general means that presents a result of the comparison, and causing the user interface to present a notification), and are similar to displaying information, which is a form of insignificant extra-solution activity. Further, the additional elements are applying the abstract ideas in a vehicle environment. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: The claim does not include additional elements that are sufficient to amount to
significantly more than the judicial exception. As discussed above with respect to Step 2A Prong
2, the additional elements amount to no more than mere instructions to apply the exception in a vehicular environment using a generic processor. Determining a difference between the observed driver and vehicle behavior and the behavior of similar drivers and their vehicles is well-understood, routine and conventional in the art, as indicated in the following rejections under 103. For these reasons, claim 10 is not patent eligible under 35 U.S.C. § 101.
As per claims 11-13, and 15-16
These system claims further define the abstract ideas of the mental processes illustrated in claim 10, they do not recite any additional elements or other limitations that transform the determinations of what data is used to make the comparison between drivers and how those comparisons are made, and these elements are well-understood, routine and conventional in the art, as indicated in the following rejections under 103.
As per claim 17
Step 1: The claim is directed to an apparatus as it recites (one or more tangible non-transitory computer-readable storage media).
Step 2A Prong 1: The claim is directed to an abstract idea of a mental process. The claim recites:
One or more tangible non-transitory computer-readable storage media storing computer- executable instructions for performing a computer process on a computing system, the computer process comprising:
receiving telematics data generated by a plurality of telematics devices disposed within a vehicle while the vehicle is being operated by a specific individual, wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices;
processing the telematics data in substantially real-time during operation of the vehicle to determine one or more driving attributes associated with the specific individual operating the vehicle based on the telematics data, wherein one or more of the driving attributes are determined at least in part by:
aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile;
comparing the one or more driving attributes associated with the specific individual operating the vehicle to one or more driving attributes associated with one or more connected users, the one or more driving attributes associated with one or more connected users received from one or more databases;
determining one or more trends of the one or more driving attributes associated with the specific individual;
causing a user interface to be generated presenting a result of the comparing; and
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed.
These limitations as drafted are simple processes that under their broadest reasonable interpretations cover the performance of these limitations in the mind or by hand or with pen and paper as these steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. The nominal recitation of the computing system does not take the limitation out of the mental process grouping. Thus, the claim recites a mental process which is an abstract idea.
Step 2A Prong 2: Judicial exception is not integrated into a practical application. The claim
recites the additional elements of:
One or more tangible non-transitory computer-readable storage media storing computer- executable instructions for performing a computer process on a computing system, the computer process comprising:
receiving telematics data generated by a plurality of telematics devices disposed within a vehicle while the vehicle is being operated by a specific individual, wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices;
processing the telematics data in substantially real-time during operation of the vehicle to determine one or more driving attributes associated with the specific individual operating the vehicle based on the telematics data, wherein one or more of the driving attributes are determined at least in part by:
aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile;
comparing the one or more driving attributes associated with the specific individual operating the vehicle to one or more driving attributes associated with one or more connected users, the one or more driving attributes associated with one or more connected users received from one or more databases;
determining one or more trends of the one or more driving attributes associated with the specific individual;
causing a user interface to be generated presenting a result of the comparing; and
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed.
The recited computer is recited at a high level of generality and merely apply the exception using generic computer components to automate the abstract idea. Further, the instruction to receive telematics data is recited at a high level of generality (i.e., as a general means of receiving telematics data), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. Further, the instruction for presenting a result of the comparing is also recited at a high level of generality (i.e., as a general means of presenting a result of the comparing, and causing the user interface to present a notification), and are similar to displaying information, which is a form of insignificant extra-solution activity. Further, the additional elements are applying the abstract ideas in a vehicle environment. Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Step 2B: The claim does not include additional elements that are sufficient to amount to
significantly more than the judicial exception. As discussed above with respect to Step 2A Prong
2, the additional elements amount to no more than mere instructions to apply the exception in a vehicular environment using a generic processor. Determining a difference between the observed driver and vehicle behavior and the behavior of similar drivers and their vehicles is well-understood, routine and conventional in the art, as indicated in the following rejections under 103. For these reasons, claim 17 is not patent eligible under 35 U.S.C. § 101.
As per claims 18, and 20
These system claims further define the abstract ideas of the mental processes illustrated in claim 17, they do not recite any additional elements or other limitations that transform the determinations of what data is used to make the comparison between drivers and how those comparisons are made, and these elements are well-understood, routine and conventional in the art, as indicated in the following rejections under 103.
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 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, 4, 10, 15, and 17 are rejected under U.S.C. § 103 as being unpatentable over Kumar, US-20220237956-A1, in view of Grandy et al., US-20220172295-A1, Park, US-20210122372-A1, and Ahn et al., US-20180182241-A1, hereinafter referred to as Kumar, Grandy, Park, and Ahn.
As per claim 1
Kumar discloses [a] computer implemented method comprising (telematics analysis (TA) computing device – Kumar ¶16):
receiving telematics data generated by a plurality of telematics devices disposed within a vehicle while the vehicle is being operated by a specific individual (receive, from a user computing device associated with the driver of the vehicle, current location data and current telematics data, systems and methods described herein may additionally or alternatively include receiving, along with measurements of geographic coordinates, telematics data (e.g., accelerometer and/or gyroscope measurements), for real-time analysis from multiple vehicles, telematics data from a plurality of user devices (e.g., mobile devices and/or other sensors mounted on or within a vehicle of a plurality of vehicles - Kumar ¶6 & ¶18 & ¶21);
processing the telematics data in substantially real-time during operation of the vehicle to determine one or more driving attributes associated with the specific individual based on the telematics data (systems and methods described herein may additionally or alternatively include receiving, along with measurements of geographic coordinates, telematics data (e.g., accelerometer and/or gyroscope measurements), for real-time analysis from multiple vehicles., TA server may determine that one user is a driver (e.g., to associate the telematics data and determined driving behaviors to the driver instead of to the passengers). – Kumar ¶18 & ¶24);
comparing the one or more driving attributes associated with the specific individual with one or more driving attributes associated with one or more connected users, the one or more driving attributes associated with one or more connected users received from one or more databases (TA server may receive telematics data from multiple user computing devices located in the same vehicle…determine that one user is a driver (e.g., to associate the telematics data and determined driving behaviors to the driver instead of to the passengers)…through matching known driving characteristics of the users with the driving characteristics of the driver (e.g., by matching driving profiles of the driver to driving profiles of each user to determine which driving profile is most similar), database 106 may include user data associated with users, telematics data of the users - Kumar ¶24 & ¶45);
generating data to cause a user interface to be generated presenting a result of the comparing (a real-time corrective action alert may be transmitted to the driver of the vehicle with respect to the detection of aggressive and/or aberrant driving behaviors of the driver and/or other users - Kumar ¶3).
Kumar does not specifically disclose wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices.
However, Grandy teaches wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices (telematics application 310, which can run on internal computing system 110A and/or client device 110B, can obtain vehicle state data 430 from one or more sensors and send vehicle state data 430 to telematics system 120. Vehicle state data 430 can include measurements captured during trip 400 and associated timestamps - Grandy ¶46).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Grandy teaches a system and method for aggregating telematics data and classifying vehicle operations.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with a system and method for aggregating telematics data and classifying vehicle operations, as taught by Grandy, with a reasonable expectation of success to better understand, manage, and/or correlate aspects of the vehicle's behavior or the driver's operation of the vehicle, and to better understand and/or model an overall behavior and/or operation of the vehicle, see Grandy ¶28 and ¶29 for details.
Kumar does not specifically disclose wherein one or more of the driving attributes are determined at least in part by: aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile.
However, Park teaches wherein one or more of the driving attributes are determined at least in part by: aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile (function of the V2X module may be replaced through a telematics module or the navigation system 210, calculate target braking power required for a braking section (i.e., an engaging phase, a deceleration phase, and a release phase) based on the estimated predicted speed profile and the predicted braking force and may calculate braking power of the main driving wheel (generally, a front wheel) based on the calculated target braking power - Park Fig 6 + ¶45 & ¶63).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Park teaches an eco-friendly vehicle and a method of controlling braking for the same.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with an eco-friendly vehicle and a method of controlling braking for the same, as taught by Park, with a reasonable expectation of success for lowering emissions and variably distribute driving force during braking by predicting braking power, thereby enhancing regenerative brake efficiency, see Park ¶4 & ¶78 for details.
Kumar does not specifically disclose determining one or more trends of the one or more driving attributes associated with the specific individual;
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed.
However, Ahn teaches determining one or more trends of the one or more driving attributes associated with the specific individual (vehicle 100 may generate the driving guide information as illustrated in FIG. 5(b) and display the driving guide information on the cluster screen 110…even if the vehicle 100 runs similarly to the B curve after the driving pattern is changed - Ahn ¶124);
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed (vehicle 100 may generate the driving guide information as illustrated in FIG. 5(b) and display the driving guide information on the cluster screen 110…even if the vehicle 100 runs similarly to the B curve after the driving pattern is changed - Ahn ¶124).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Ahn teaches a method for displaying driving guide information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with a method for displaying driving guide information of a vehicle, as taught by Ahn, with a reasonable expectation of success for improving the convenience of a driver, and to improve the fuel efficiency, see Ahn ¶3 & ¶66 for details.
As per claim 2
Kumar further discloses wherein a telematics device of the plurality of telematics devices is a computing device of the vehicle (receive, from a user computing device associated with the driver of the vehicle, current location data and current telematics data, systems and methods described herein may additionally or alternatively include receiving, along with measurements of geographic coordinates, telematics data (e.g., accelerometer and/or gyroscope measurements), for real-time analysis from multiple vehicles, telematics data from a plurality of user devices (e.g., mobile devices and/or other sensors mounted on or within a vehicle of a plurality of vehicles - Kumar ¶6 & ¶18 & ¶21).
As per claim 4
Kumar further discloses wherein a telematics device of the plurality of the telematics devices is a mobile computing device (receive, from a user computing device associated with the driver of the vehicle, current location data and current telematics data, systems and methods described herein may additionally or alternatively include receiving, along with measurements of geographic coordinates, telematics data (e.g., accelerometer and/or gyroscope measurements), for real-time analysis from multiple vehicles, telematics data from a plurality of user devices (e.g., mobile devices and/or other sensors mounted on or within a vehicle of a plurality of vehicles - Kumar ¶6 & ¶18 & ¶21).
As per claim 10
Kumar discloses [a] system comprising: at least one processor configured to (telematics analysis (TA) computing device – Kumar ¶16):
receiving telematics data generated by a plurality of telematics devices disposed within a vehicle while the vehicle is being operated by a specific individual (receive, from a user computing device associated with the driver of the vehicle, current location data and current telematics data, systems and methods described herein may additionally or alternatively include receiving, along with measurements of geographic coordinates, telematics data (e.g., accelerometer and/or gyroscope measurements), for real-time analysis from multiple vehicles, telematics data from a plurality of user devices (e.g., mobile devices and/or other sensors mounted on or within a vehicle of a plurality of vehicles - Kumar ¶6 & ¶18 & ¶21);
process the telematics data in substantially real-time during operation of the vehicle to determine one or more driving attributes associated with the specific individual based on the telematics data (systems and methods described herein may additionally or alternatively include receiving, along with measurements of geographic coordinates, telematics data (e.g., accelerometer and/or gyroscope measurements), for real-time analysis from multiple vehicles., TA server may determine that one user is a driver (e.g., to associate the telematics data and determined driving behaviors to the driver instead of to the passengers). – Kumar ¶18 & ¶24);
comparing the one or more driving attributes associated with the specific individual with one or more driving attributes associated with one or more connected users, the one or more driving attributes associated with one or more connected users received from one or more databases (TA server may receive telematics data from multiple user computing devices located in the same vehicle…determine that one user is a driver (e.g., to associate the telematics data and determined driving behaviors to the driver instead of to the passengers)…through matching known driving characteristics of the users with the driving characteristics of the driver (e.g., by matching driving profiles of the driver to driving profiles of each user to determine which driving profile is most similar), database 106 may include user data associated with users, telematics data of the users - Kumar ¶24 & ¶45);
cause a user interface to be generated that presents a result of the comparison (analyze additional telematics data (e.g., real-time telematics data from a plurality of drivers) to reveal driving behaviors of drivers. Such driving events may trigger real-time notifications via a messaging server (e.g., SMS, email, etc.) to notify the driver and encourage safer driving habits/reducing accidents…if most drivers on a certain stretch of road are going between 25 miles per hour and 32 miles per hour, and one driver is determined to be going 60 miles per hour on the same stretch of road, the TA server may determine that the driver poses an accident risk and send a real-time notification to other drivers around the erratic driver - Kumar ¶33).
Kumar does not specifically disclose wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices.
However, Grandy teaches wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices (telematics application 310, which can run on internal computing system 110A and/or client device 110B, can obtain vehicle state data 430 from one or more sensors and send vehicle state data 430 to telematics system 120. Vehicle state data 430 can include measurements captured during trip 400 and associated timestamps - Grandy ¶46).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Grandy teaches a system and method for aggregating telematics data and classifying vehicle operations.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with a system and method for aggregating telematics data and classifying vehicle operations, as taught by Grandy, with a reasonable expectation of success to better understand, manage, and/or correlate aspects of the vehicle's behavior or the driver's operation of the vehicle, and to better understand and/or model an overall behavior and/or operation of the vehicle, see Grandy ¶28 and ¶29 for details.
Kumar does not specifically disclose wherein one or more of the driving attributes are determined at least in part by: aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile.
However, Park teaches wherein one or more of the driving attributes are determined at least in part by: aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile (function of the V2X module may be replaced through a telematics module or the navigation system 210, calculate target braking power required for a braking section (i.e., an engaging phase, a deceleration phase, and a release phase) based on the estimated predicted speed profile and the predicted braking force and may calculate braking power of the main driving wheel (generally, a front wheel) based on the calculated target braking power - Park Fig 6 + ¶45 & ¶63).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Park teaches an eco-friendly vehicle and a method of controlling braking for the same.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with an eco-friendly vehicle and a method of controlling braking for the same, as taught by Park, with a reasonable expectation of success for lowering emissions and variably distribute driving force during braking by predicting braking power, thereby enhancing regenerative brake efficiency, see Park ¶4 & ¶78 for details.
Kumar does not specifically disclose determining one or more trends of the one or more driving attributes associated with the specific individual;
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed.
However, Ahn teaches determining one or more trends of the one or more driving attributes associated with the specific individual (vehicle 100 may generate the driving guide information as illustrated in FIG. 5(b) and display the driving guide information on the cluster screen 110…even if the vehicle 100 runs similarly to the B curve after the driving pattern is changed - Ahn ¶124);
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed (vehicle 100 may generate the driving guide information as illustrated in FIG. 5(b) and display the driving guide information on the cluster screen 110…even if the vehicle 100 runs similarly to the B curve after the driving pattern is changed - Ahn ¶124).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Ahn teaches a method for displaying driving guide information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with a method for displaying driving guide information of a vehicle, as taught by Ahn, with a reasonable expectation of success for improving the convenience of a driver, and to improve the fuel efficiency, see Ahn ¶3 & ¶66 for details.
As per claim 15
Kumar further discloses wherein a telematics device of the plurality of telematics devices is one of a computing device of the vehicle or a mobile computing device (receive, from a user computing device associated with the driver of the vehicle, current location data and current telematics data, systems and methods described herein may additionally or alternatively include receiving, along with measurements of geographic coordinates, telematics data (e.g., accelerometer and/or gyroscope measurements), for real-time analysis from multiple vehicles, telematics data from a plurality of user devices (e.g., mobile devices and/or other sensors mounted on or within a vehicle of a plurality of vehicles - Kumar ¶6 & ¶18 & ¶21).
As per claim 17
Kumar discloses [o]ne or more tangible non-transitory computer-readable storage media storing computer- executable instructions for performing a computer process on a computing system, the computer process comprising (disclosure may be implemented using computer programming or engineering techniques including computer software, firmware, hardware or any combination or subset thereof - Kumar ¶90):
receiving telematics data generated by a plurality of telematics devices disposed within a vehicle while the vehicle is being operated by a specific individual (receive, from a user computing device associated with the driver of the vehicle, current location data and current telematics data, systems and methods described herein may additionally or alternatively include receiving, along with measurements of geographic coordinates, telematics data (e.g., accelerometer and/or gyroscope measurements), for real-time analysis from multiple vehicles, telematics data from a plurality of user devices (e.g., mobile devices and/or other sensors mounted on or within a vehicle of a plurality of vehicles - Kumar ¶6 & ¶18 & ¶21);
processing the telematics data in substantially real-time during operation of the vehicle to determine one or more driving attributes associated with the specific individual based on the telematics data (systems and methods described herein may additionally or alternatively include receiving, along with measurements of geographic coordinates, telematics data (e.g., accelerometer and/or gyroscope measurements), for real-time analysis from multiple vehicles., TA server may determine that one user is a driver (e.g., to associate the telematics data and determined driving behaviors to the driver instead of to the passengers). – Kumar ¶18 & ¶24);
comparing the one or more driving attributes associated with the specific individual with one or more driving attributes associated with one or more connected users, the one or more driving attributes associated with one or more connected users received from one or more databases (TA server may receive telematics data from multiple user computing devices located in the same vehicle…determine that one user is a driver (e.g., to associate the telematics data and determined driving behaviors to the driver instead of to the passengers)…through matching known driving characteristics of the users with the driving characteristics of the driver (e.g., by matching driving profiles of the driver to driving profiles of each user to determine which driving profile is most similar), database 106 may include user data associated with users, telematics data of the users - Kumar ¶24 & ¶45);
causing a user interface to be generated presenting a result of the comparing (analyze additional telematics data (e.g., real-time telematics data from a plurality of drivers) to reveal driving behaviors of drivers. Such driving events may trigger real-time notifications via a messaging server (e.g., SMS, email, etc.) to notify the driver and encourage safer driving habits/reducing accidents…if most drivers on a certain stretch of road are going between 25 miles per hour and 32 miles per hour, and one driver is determined to be going 60 miles per hour on the same stretch of road, the TA server may determine that the driver poses an accident risk and send a real-time notification to other drivers around the erratic driver - Kumar ¶33).
Kumar does not specifically disclose wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices.
However, Grandy teaches wherein the telematics data comprises timestamped sensor data generated by a plurality of sensors associated respectively with the plurality of telematics devices (telematics application 310, which can run on internal computing system 110A and/or client device 110B, can obtain vehicle state data 430 from one or more sensors and send vehicle state data 430 to telematics system 120. Vehicle state data 430 can include measurements captured during trip 400 and associated timestamps - Grandy ¶46).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Grandy teaches a system and method for aggregating telematics data and classifying vehicle operations.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with a system and method for aggregating telematics data and classifying vehicle operations, as taught by Grandy, with a reasonable expectation of success to better understand, manage, and/or correlate aspects of the vehicle's behavior or the driver's operation of the vehicle, and to better understand and/or model an overall behavior and/or operation of the vehicle, see Grandy ¶28 and ¶29 for details.
Kumar does not specifically disclose wherein one or more of the driving attributes are determined at least in part by: aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile.
However, Park teaches wherein one or more of the driving attributes are determined at least in part by: aligning timestamped sensor data associated with vehicle braking with timestamped sensor data associated with vehicle speed to ascertain a braking with respect to speed profile (function of the V2X module may be replaced through a telematics module or the navigation system 210, calculate target braking power required for a braking section (i.e., an engaging phase, a deceleration phase, and a release phase) based on the estimated predicted speed profile and the predicted braking force and may calculate braking power of the main driving wheel (generally, a front wheel) based on the calculated target braking power - Park Fig 6 + ¶45 & ¶63).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Park teaches an eco-friendly vehicle and a method of controlling braking for the same.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with an eco-friendly vehicle and a method of controlling braking for the same, as taught by Park, with a reasonable expectation of success for lowering emissions and variably distribute driving force during braking by predicting braking power, thereby enhancing regenerative brake efficiency, see Park ¶4 & ¶78 for details.
Kumar does not specifically disclose determining one or more trends of the one or more driving attributes associated with the specific individual;
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed.
However, Ahn teaches determining one or more trends of the one or more driving attributes associated with the specific individual (vehicle 100 may generate the driving guide information as illustrated in FIG. 5(b) and display the driving guide information on the cluster screen 110…even if the vehicle 100 runs similarly to the B curve after the driving pattern is changed - Ahn ¶124);
causing the user interface to present a notification indicating that the one or more trends associated with the specific individual have changed (vehicle 100 may generate the driving guide information as illustrated in FIG. 5(b) and display the driving guide information on the cluster screen 110…even if the vehicle 100 runs similarly to the B curve after the driving pattern is changed - Ahn ¶124).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Ahn teaches a method for displaying driving guide information of a vehicle.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with a method for displaying driving guide information of a vehicle, as taught by Ahn, with a reasonable expectation of success for improving the convenience of a driver, and to improve the fuel efficiency, see Ahn ¶3 & ¶66 for details.
Claims 3, and 5 are rejected under U.S.C. § 103 as being unpatentable over Kumar, Grandy, in view of Park, and Ahn, as per claims 1, and 2, respectively, and further in view of Gross et al., US-20230387481-A1, hereinafter referred to as Gross.
As per claim 3
Kumar does not specifically disclose wherein the telematics device is an on-board diagnostics device installed at the vehicle.
However, Gross teaches wherein the telematics device is an on-board diagnostics device installed at the vehicle (vehicle telematics system…sensors and/or subsystems configured to collect any one or more types of telematics data, such as…on-board diagnostic information - Gross ¶26).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Gross teaches systems and methods for monitoring a battery of an EV based upon collected data associated with operation of the EV.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with systems and methods for monitoring a battery of an EV based upon collected data associated with operation of the EV, as taught by Gross 481, with a reasonable expectation of success to generate a distraction score, and improve driving performance, see Gross ¶34 & ¶38 for details.
As per claim 5
Kumar further discloses location data (GPS location data – Kumar ¶3).
Kumar does not specifically disclose wherein: the telematics data generated by one or more of the plurality of telematics devices includes: acceleration data.
However, Gross teaches wherein: the telematics data generated by one or more of the plurality of telematics devices includes: acceleration data (telematics data may pertain to driving events (e.g., acceleration, braking, cornering, direction, and speed), receiving, by the one or more processors and from an electronic device associated with the EV, telematics data - Gross ¶6 & ¶8).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Gross teaches systems and methods for monitoring a battery of an EV based upon collected data associated with operation of the EV.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with systems and methods for monitoring a battery of an EV based upon collected data associated with operation of the EV, as taught by Gross 481, with a reasonable expectation of success to generate a distraction score, and improve driving performance, see Gross ¶34 & ¶38 for details.
Claims 6, and 11 are rejected under U.S.C. § 103 as being unpatentable over Kumar, Grandy, in view of Park, and Ahn, as per claims 1, and 10, respectively, and further in view of Harvey et al., US-10703379-B1, hereinafter referred to as Harvey.
As per claim 6
Kumar does not specifically disclose wherein the one or more driving attributes include one or more of: an amount of vehicle driving time; an amount of operator driving time; a rate of braking; a driving speed at a time of braking; a driving time of day; a recurring driving event; a percent of miles above or below a speed limit; distance that the vehicle travelled; and an amount of phone handling.
However, Harvey teaches wherein the one or more driving attributes include one or more of: an amount of vehicle driving time; an amount of operator driving time; a rate of braking; a driving speed at a time of braking; a driving time of day; a recurring driving event; a percent of miles above or below a speed limit; distance that the vehicle travelled; and an amount of phone handling (telematics data corresponding to the vehicle owner's driving behavior…deceleration rate during braking, distance to stop – Harvey Column 8 Lines 2-7).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Harvey teaches vehicle renting/sharing, and predicting user preferences based on telematics data.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with vehicle renting/sharing, and predicting user preferences based on telematics data, as taught by Harvey, with a reasonable expectation of success to define a “safe” baseline driving behavior for the particular portion of the roadway, see Harvey Column 10 Lines 2-4 for details.
As per claim 11
Kumar does not specifically disclose wherein the one or more driving attributes include a rate of braking associated with a distance that the vehicle travelled.
However, Harvey teaches wherein the one or more driving attributes include a rate of braking associated with a distance that the vehicle travelled (telematics data corresponding to the vehicle owner's driving behavior…deceleration rate during braking, distance to stop – Harvey Column 8 Lines 2-7).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Harvey teaches vehicle renting/sharing, and predicting user preferences based on telematics data.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with vehicle renting/sharing, and predicting user preferences based on telematics data, as taught by Harvey, with a reasonable expectation of success to define a “safe” baseline driving behavior for the particular portion of the roadway, see Harvey Column 10 Lines 2-4 for details.
Claims 8 and 16 are rejected under U.S.C. § 103 as being unpatentable over Kumar, Grandy, in view of Park, and Ahn, as per claims 1, and 10, respectively, and further in view of Rosenbaum, US-20230060300-A1, hereinafter referred to as Rosenbaum.
As per claim 8
Kumar does not specifically disclose wherein the comparing the one or more driving attributes associated with the specific individual to the one or more driving attributes associated with one or more connected users includes comparing the one or more driving attributes associated with the specific individual to a statistical average of the one or more driving attributes associated with one or more connected users.
However, Rosenbaum teaches wherein the comparing the one or more driving attributes associated with the specific individual to the one or more driving attributes associated with one or more connected users includes comparing the one or more driving attributes associated with the specific individual to a statistical average of the one or more driving attributes associated with one or more connected users (driving behavior…human driver of the vehicle can then be compared to the average driving behavior of the driving units and/or human drivers of the reference vehicles, i.e. to a norm, in order to derive the at least one driving quantity. - Rosenbaum ¶110).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Rosenbaum teaches a method and a system for analyzing the control of a vehicle comprising an autonomous driving unit.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with a method and a system for analyzing the control of a vehicle comprising an autonomous driving unit, as taught by Rosenbaum, with a reasonable expectation of success for improving operation of a vehicle containing an autonomous driving unit configured for autonomously controlling the vehicle and a control takeover management unit configured for passing over control to a human driver, see Rosenbaum ¶139 for details.
As per claim 16
Kumar does not specifically disclose wherein the one or more driving attributes associated with the specific individual are compared with a statistical average of the one or more driving attributes associated with one or more connected users.
However, Rosenbaum teaches wherein the one or more driving attributes associated with the specific individual are compared with a statistical average of the one or more driving attributes associated with one or more connected users (driving behavior… human driver of the vehicle can then be compared to the average driving behavior of the driving units and/or human drivers of the reference vehicles, i.e. to a norm, in order to derive the at least one driving quantity. - Rosenbaum ¶110).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Rosenbaum teaches a method and a system for analyzing the control of a vehicle comprising an autonomous driving unit.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with a method and a system for analyzing the control of a vehicle comprising an autonomous driving unit, as taught by Rosenbaum, with a reasonable expectation of success for improving operation of a vehicle containing an autonomous driving unit configured for autonomously controlling the vehicle and a control takeover management unit configured for passing over control to a human driver, see Rosenbaum ¶139 for details.
Claims 9, 12, 13, 18, and 20 are rejected under U.S.C. § 103 as being unpatentable over Kumar, in view of Grandy, Park, and Ahn, as per claims 1, 10, and 17, respectively, and further in view of Bourne et al., US-20140067434-A1, hereinafter referred to as Bourne.
As per claim 9
Kumar does not specifically disclose wherein the comparing the one or more driving attributes associated with the specific individual to the one or more driving attributes associated with one or more connected users includes comparing the one or more driving attributes associated with the specific individual to a normal distribution of the one or more driving attributes associated with one or more connected users.
However, Bourne teaches wherein the comparing the one or more driving attributes associated with the specific individual to the one or more driving attributes associated with one or more connected users includes comparing the one or more driving attributes associated with the specific individual to a normal distribution of the one or more driving attributes associated with one or more connected users (determined driver characteristics of the driver are compared to a normal distribution curve of driving characteristic data, the normal distribution curve is determined for driving characteristic data of a plurality of drivers at each of the one or more locations - Bourne ¶12 & ¶28).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Bourne teaches methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics, as taught by Bourne, with a reasonable expectation of success for determining a risk profile of a driver of a vehicle using improved driver metrics, see Bourne ¶12 for details.
As per claim 12
Kumar does not specifically disclose wherein the one or more driving attributes include a driving time of day associated with a distance that the vehicle travelled.
However, Bourne teaches wherein the one or more driving attributes include a driving time of day associated with a distance that the vehicle travelled (determined characteristics of the driver can be at least one of speed, time of day, acceleration, braking, an amount of times that brakes are used, and an amount of times that the driver accelerates - Bourne ¶13).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Bourne teaches methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics, as taught by Bourne, with a reasonable expectation of success for determining a risk profile of a driver of a vehicle using improved driver metrics, see Bourne ¶12 for details.
As per claim 13
Kumar does not specifically disclose wherein the one or more driving attributes include a driving speed associated with a distance that the vehicle travelled.
However, Bourne teaches wherein the one or more driving attributes include a driving speed associated with a distance that the vehicle travelled (determined characteristics of the driver can be at least one of speed, time of day, acceleration, braking, an amount of times that brakes are used, and an amount of times that the driver accelerates - Bourne ¶13).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Bourne teaches methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics, as taught by Bourne, with a reasonable expectation of success for determining a risk profile of a driver of a vehicle using improved driver metrics, see Bourne ¶12 for details.
As per claim 18
Kumar does not specifically disclose wherein the one or more driving attributes associated with the specific individual operating the vehicle include: an amount of driven miles associated with the vehicle; and a driving speed associated with the specific individual.
However, Bourne teaches wherein the one or more driving attributes associated with the specific individual operating the vehicle include: an amount of driven miles associated with the vehicle; and a driving speed associated with the specific individual (determined characteristics of the driver can be at least one of speed, time of day, acceleration, braking, an amount of times that brakes are used, and an amount of times that the driver accelerates, to obtain a risk profile for a vehicle driver is the Driverscore, which looks at various driving behaviors…Some of the measured variables in UBI include: number of miles driven, the UBI device/methods will examine the driver to see if driving behavior is changed as a result - Bourne ¶13 & ¶48 & ¶52).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Bourne teaches methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics, as taught by Bourne, with a reasonable expectation of success for determining a risk profile of a driver of a vehicle using improved driver metrics, see Bourne ¶12 for details.
As per claim 20
Kumar does not specifically disclose wherein the comparing the one or more driving attributes associated with the specific individual operating the vehicle to the one or more driving attributes associated with one or more connected users includes comparing the one or more driving attributes associated with the specific individual operating the vehicle to a normal distribution of the one or more driving attributes associated with one or more connected users.
However, Bourne teaches wherein the comparing the one or more driving attributes associated with the specific individual operating the vehicle to the one or more driving attributes associated with one or more connected users includes comparing the one or more driving attributes associated with the specific individual operating the vehicle to a normal distribution of the one or more driving attributes associated with one or more connected users (determined driver characteristics of the driver are compared to a normal distribution curve of driving characteristic data, the normal distribution curve is determined for driving characteristic data of a plurality of drivers at each of the one or more locations - Bourne ¶12 & ¶28).
Kumar discloses systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents. Bourne teaches methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Kumar, systems and methods for monitoring driver behavior for drivers of a vehicle using telematics data so as to prevent and/or reduce accidents, with methods and systems related to usage-based insurance to determine a risk profile using improved driver metrics, as taught by Bourne, with a reasonable expectation of success for determining a risk profile of a driver of a vehicle using improved driver metrics, see Bourne ¶12 for details.
Conclusion
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/F.A.S./Examiner, Art Unit 3668
/Fadey S. Jabr/Supervisory Patent Examiner, Art Unit 3668