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 .
Claim Objections
Claim 1 is objected to because of the following informalities: Claim 1 contains a limitation of “correcting a drift of a gyroscope using data from accelerometer of the personal device during the determined time of stable dynamics.” Applicant should clarify whether “a gyroscope” as quoted in this limitation means the same gyroscope mentioned earlier in Claim 1. Appropriate correction is required.
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.
Claim 9 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
The determination of whether a claim recites patent ineligible subject matter is a 2-step inquiry.
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), see MPEP 2106.03, or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis: see MPEP 2106.04
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon? see MPEP 2106.04(II)(A)(1)
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? see MPEP 2106.04(II)(A)(2)
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? see MPEP 2106.05
101 Analysis – Step 1
Claim 9 is directed to a method of controlling a vehicle (i.e., a process). Therefore, claim 1 is within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis, 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. see MPEP 2106(A)(II)(1) and MPEP 2106.04(a)-(c)
Independent claim 9 includes limitations that recite an abstract idea (emphasized below [with the category of abstract idea in brackets]) and will be used as a representative claim for the remainder of the 101 rejection. Claim 9 recites:
A method for estimating road geometry features using crowd-sourced sensor data, comprising:
collecting gyroscope data, accelerometer data, and GPS data from a plurality of trips over a road segment;
aggregating the accelerometer data from each trip;
correcting each of the gyroscope data using the aggregated accelerometer data [mental process/step];
aggregating the corrected gyroscope data; and
determining the road geometry features based on the aggregated gyroscope data [mental process/step].
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “evaluating…” in the context of this claim encompasses a person (driver) looking at data collected and forming a simple judgement. Accordingly, the claim recites at least one abstract idea.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. see MPEP 2106.04(II)(A)(2) and MPEP 2106.04(d)(2). It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” [with a description of the additional limitations in brackets], while the bolded portions continue to represent the “abstract idea”.):
A method for estimating road geometry features using crowd-sourced sensor data, comprising:
collecting gyroscope data, accelerometer data, and GPS data from a plurality of trips over a road segment [pre-solution activity (data gathering) using generic sensors];
aggregating the accelerometer data from each trip [pre-solution activity (data gathering)];
correcting each of the gyroscope data using the aggregated accelerometer data [mental process/step];
aggregating the corrected gyroscope data [pre-solution activity (data gathering)]; and
determining the road geometry features based on the aggregated gyroscope data [mental process/step].
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 “collecting gyroscope data…,” and aggregating the data, the examiner submits that these limitations are insignificant extra-solution activities that merely use a set of sensors and a computer processor and storage to perform the process. In particular, the receiving steps from the sensors are recited at a high level of generality (i.e. as a general means of gathering vehicle and road condition data for use in the evaluating step), and amount to mere data gathering, which is a form of insignificant extra-solution activity.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitations as an ordered combination or as a whole, the limitations add nothing that is not 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. see MPEP § 2106.05. Accordingly, the additional limitations do 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 9 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 element of using a vehicle controller to perform the evaluating… amounts to nothing more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of “collecting gyroscope data…,” and aggregating the data, the examiner submits that these limitations are insignificant extra-solution activities. In addition, these additional limitations (and the combination, thereof) amount to no more than what is well-understood, routine and conventional activity. Hence, the claim is not patent eligible.
Therefore, claim 9 is ineligible under 35 USC §101.
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 1-12 are rejected under 35 U.S.C. 103 as being unpatentable over Gazza, et al., US 2020/0003557 A1, in view of Breed, et al., US 2019/0271550 A1.
As per Claim 1, Gazza teaches a method for collecting road geometry information (¶ 24; “for measuring distances in the range of typical vehicle ride height”), comprising:
obtaining gyroscope data from a gyroscope of a personal device fixed to a moving vehicle (¶ 26); aligning the gyroscope data with GPS data from a GPS module of the personal device to generate aligned data (¶¶ 27-28);
matching the aligned data to a nearest road segment based on a preexisting map (¶ 27-28; based on “road grade information stored in the database” and “geolocation points”); and determining a time of stable dynamics of the vehicle based on the map and the matched nearest road segment (¶¶ 76; per testing with dynamometer 120 of Figure 1B).
Gazza does not expressly teach correcting a drift of a gyroscope using data from an accelerometer of the personal device during the determined time of stable dynamics. Breed teaches correcting a drift of a gyroscope using data from an accelerometer of the personal device during the determined time of stable dynamics (¶¶ 196-197, 239). At the time of the invention, a person of skill in the art would have thought it obvious to combine the gyroscope collection process of Gazza with the adjustment steps of Breed, in order to include road hazards or other potentially dangerous conditions in future mappings.
As per Claim 2, Gazza does not expressly teach that a pitch drift of the gyroscope is corrected. Breed teaches that a pitch drift of the gyroscope is corrected (¶ 63). See Claim 1 above for the rationale based on obviousness, motivations and reasons to combine.
As per Claim 3, Gazza teaches obtaining an elevation profile using a preexisting elevation database (¶ 10).
As per Claim 4, Gazza does not expressly teach that a roll drift of the gyroscope is corrected. Breed teaches that a roll drift of the gyroscope is corrected (¶¶ 229-230, 272-273). See Claim 1 above for the rationale based on obviousness, motivations and reasons to combine.
As per Claim 5, Gazza does not expressly teach that a yaw drift of the gyroscope is corrected. Breed teach that a yaw drift of the gyroscope is corrected (¶¶ 229-231). See Claim 1 above for the rationale based on obviousness, motivations and reasons to combine.
As per Claim 6, Gazza teaches translating the aligned data from a personal device coordinate system to a vehicle coordinate system (¶¶ 27-28).
As per Claim 7, Gazza does not expressly teach that translating the aligned data comprises: calculating a gravity vector when the vehicle is stationary; and calculating a vehicle forward direction vector. Breed teaches that translating the aligned data comprises:
calculating a gravity vector when the vehicle is stationary (¶ 69); and
calculating a vehicle forward direction vector (¶¶ 223, 301).
See Claim 1 above for the rationale based on obviousness, motivations and reasons to combine.
As per Claim 8, Gazza does not expressly teach that the gyroscope data is aligned with the GPS data by peak matching. Breed teaches that the gyroscope data is aligned with the GPS data by peak matching (¶¶ 293-294). See Claim 1 above for the rationale based on obviousness, motivations and reasons to combine.
As per Claim 9, Gazza teaches a method for estimating road geometry features using crowd-sourced sensor data (¶¶ 26-28), comprising:
collecting gyroscope data, accelerometer data, and GPS data from a plurality of trips over a road segment (¶ 26); and
aggregating the accelerometer data from each trip (¶ 26).
Gazza does not expressly teach: correcting each of the gyroscope data using the aggregated accelerometer data; aggregating the corrected gyroscope data; and determining the road geometry features based on the aggregated gyroscope data. Breed teaches:
correcting each of the gyroscope data using the aggregated accelerometer data (¶¶ 196-197, 239);
aggregating the corrected gyroscope data (¶ 218); and
determining the road geometry features based on the aggregated gyroscope data (¶ 220).
See Claim 1 above for the rationale based on obviousness, motivations and reasons to combine.
As per Claim 10, Gazza teaches a method for speed control of a vehicle (¶¶ 26-28), comprising:
receiving a vehicle velocity and control acceleration signal (¶ 31).
Gazza does not expressly teach: receiving a speed limit signal and a road grade profile for a current long epoch; determining a long-term velocity target and long-term acceleration target for the current long epoch based on the vehicle velocity, the control acceleration signal, the speed limit signal, and the road grade profile; receiving vertical curve information for a current short epoch; determining a short-term acceleration target for the current short epoch based on the long- term velocity target and long-term acceleration target, and the vertical curve information; and controlling a vehicle acceleration based on a combination of the short-term acceleration target and the long-term acceleration target. Breed teaches:
receiving a speed limit signal and a road grade profile for a current long epoch (¶ 48);
determining a long-term velocity target and long-term acceleration target for the current long epoch based on the vehicle velocity, the control acceleration signal, the speed limit signal, and the road grade profile (¶ based on “travel lanes, instructions or limitations provided or imposed by traffic control devices, etc.”);
receiving vertical curve information for a current short epoch (¶ 196);
determining a short-term acceleration target for the current short epoch based on the long-term velocity target and long-term acceleration target, and the vertical curve information (¶¶ 238-239); and
controlling a vehicle acceleration based on a combination of the short-term acceleration target and the long-term acceleration target (¶ 255).
See Claim 1 above for the rationale based on obviousness, motivations and reasons to combine.
As per Claim 11, Gazza does not expressly teach adjusting the long-term acceleration target by a first jerk constraint, wherein the first jerk constraint is selected from values between a 40th and 60th percentile of a set of driver values. Breed teaches adjusting the long-term acceleration target by a first jerk constraint, wherein the first jerk constraint is selected from values between a 40th and 60th percentile of a set of driver values (¶¶ 339-340, 347-348; based on “angular velocity and linear acceleration data”). See Claim 1 above for the rationale based on obviousness, motivations and reasons to combine.
As per Claim 12, Gazza does not expressly teach adjusting the short-term acceleration target by a second jerk constraint, wherein the second jerk constraint is selected from values between a 70th and 90th percentile of a set of driver values. Breed teaches adjusting the short-term acceleration target by a second jerk constraint, wherein the second jerk constraint is selected from values between a 70th and 90th percentile of a set of driver values (¶¶ 339-340, 347-348; based on “angular velocity and linear acceleration data”). See Claim 1 above for the rationale based on obviousness, motivations and reasons to combine.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ATUL TRIVEDI whose telephone number is (313)446-4908. The examiner can normally be reached Mon-Fri; 9:00 AM-5:00 PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Peter Nolan can be reached at (571) 270-7016. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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ATUL TRIVEDI
Primary Examiner
Art Unit 3661
/ATUL TRIVEDI/Primary Examiner, Art Unit 3661