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 .
The current application filed on May 15, 2024.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Independent claims:
Claim 1. A method comprising:
obtaining sensor data generated using one or more sensors of a machine, the sensor data representative of one or more lanes of a driving surface within an environment;
computing, based at least on the sensor data, a first vector representing, from a first side of the driving surface, one or more first probabilities that the machine is located within the one or more lanes; and
computing, based at least on the sensor data, a second vector representing, from a second side of the driving surface different from the first side of the driving surface, one or more second probabilities that the machine is located within the one or more lanes;
localizing, based at least on the first vector and the second vector, the machine to a lane of the one or more lanes; and
causing the machine to perform one or more operations based at least on the machine being in the lane.
Claim 7. A system comprising: one or more processors to:
determine, based at least on sensor data obtained using one or more sensors of a machine, a first output indicating, from a first side of a driving surface, one or more first probabilities that the machine is located within one or more lanes and a second output indicating, from a second side of the driving surface, one or more second probabilities that the machine is located within the one or more lanes; and
cause, based at least on the first output and the second output, the machine to perform one or more operations.
Claim 18. One or more processors comprising:
processing circuitry to cause a machine to perform one or more operations based at least on localizing a machine to a lane, wherein the lane is determined based at least on a first output indicating one or more first probabilities that the machine is located within one or more first lanes and a second output indicating one or more second probabilities that the machine is located within one or more second lanes, the first output being associated with a first side of a driving surface and the second output being associated with a second side of the driving surface.
101 Analysis - Step 1: Statutory category – Yes
Claims 1-20 recites a method/system comprises one or more processing circuit. The claim falls within one of the four statutory categories. MPEP 2106.03
101 Analysis - Step 2A Prong one evaluation: Judicial Exception – Yes – Mental processes.
In Step 2A, Prong one of the 2019 Patent Eligibility Guidance (PEG), a claim is to be analyzed to determine whether it recites subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) mental processes, and/or c) certain methods of organizing human activity.
The Office submits that the foregoing bolded limitation(s) constitutes judicial exceptions in terms of “mental processes” because under its broadest reasonable interpretation, the limitations can be “performed in the human mind, or by a human using a pen and paper”. See MPEP 2106.04(a)(2)(III)
The claims recite the limitation of (e.g. claim 1) “obtaining sensor data …”; “computing, based at least on the sensor data, a first vector representing…”; “computing, based at least on the sensor data, a second vector representing…”; “localizing, based at least on the first vector and the second vector…”; and “causing the machine to perform one or more operations …” This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind.
Also, e.g., claim 7 recites of “A system comprising: one or more processors to: determine, based at least on sensor data …; and cause, based at least on the first output and the second output, the machine to perform one or more operations” This limitation as drafted, is also a simple process that covers perfornace of the limitation in the mind but for the recitation of by a “processor”
And further more (e.g., claim 18) processing circuitry to cause a machine to perform one or more operations based on localizing the machine to a lane, wherein the lane determined based on outputs indicating probabilities. This limitation, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of by a “processing circuit”.
That is, other than reciting by the “processor” and/or “processing circuit” nothing in the claim elements precludes the step from practically being performed in the mind. The claim encompasses a person looking at probability data collected and forming a simple judgement. The mere nominal recitation of by the processing circuit does not take the claim limitations out of the mental process grouping.
Thus, the claim recites a mental process.
101 Analysis - Step 2A Prong two evaluation: Practical Application – No
In Step 2A, Prong two of the 2019 PEG, a claim is to be evaluated whether, as a whole, it integrates the recited judicial exception into a practical application. As noted in MPEP 2106.04(d), 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, such that the claim is more than a drafting effort designed to monopolize the judicial exception. The courts have indicated that additional elements such as: 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.”
The Office submits that the foregoing bolded limitation(s) recite additional elements that do not integrate the recited judicial exception into a practical application.
The claim recites additional elements or steps of causing a machine to perform one or more operation based on the machine localized to a lane, wherein the lane is determined based on outputs indicating probability the machine located. The lane is determined step from the outputs indicated probabilities are recited at as a general means of gathering road condition with probability data for use in the determining step which is a form of insignificant extra-solution activity. The causing a machine to perform one or more operation as a general means of a post solution, which is a form of insignificant extra-solution activity. The processor comprises a processing circuit merely describes how to generally “apply” the otherwise mental judgements using a generic or general-purpose vehicle control environment, i.e. a computer.
Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
101 Analysis - Step 2B evaluation: Inventive concept – No
In Step 2B of the 2019 PEG, a claim is to be evaluated as to whether the claim, as a whole, amounts to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception on a generic computer cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, the determing step and the causing the machine to perform one or more operations step were considered to be insignificant extra-solution activity in Step 2A, and thus they are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The current application’s background recites that vehicles to operate safety in environments must be capable of effectively performing various vehicle maneuvers such as lane keeping, lane changing, and etc. (see [0001]), and the claims’ specification does not provide any indication that the vehicle (machine) is anything other than a conventional computer within a vehicle. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Further, the Federal Circuit in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere causing the vehicle performing one or more operations is a well understood, routine, and conventional function. Accordingly, a conclusion that the collecting step is well-understood, routine, conventional activity is supported under Berkheimer.
Thus, the claims are ineligible.
Dependent Claims
Dependent claims(s) 2-6, 8-17 & 19-20 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of the dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application. Therefore, dependent claims 2-6, 8-17 & 19-20 are not patent eligible under the same rationale as provided for in the rejection of 18.
Therefore, claim(s) 1-20 is/are ineligible under 35 USC §101.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 18-20 are rejected under 35 U.S.C. 112, first paragraph, as failing to comply with the enablement requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention.
Claim 18 contains a single means claim (“One or more processor comprising: processing circuitry to cause a machine …”) is an undue breadth (see MPEP 2164.08(a)).
The claim cites only “processing circuitry to cause a machine to perform one or more operation …” which fails to provide an enabling disclosure because it covers all ways, and the disclosure could not be enabled for all ways, known and unknown.
The specification does not disclose any embodiment that operates only with a “processing circuitry”.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wray (20220306156) in view of Towal (20190384304).
With regard to claim 1, Wray discloses a method comprising:
obtaining sensor data generated using one or more sensors of a machine, the sensor data representative of one or more lanes of a driving surface within an environment (vehicle 100 includes a sensor system 136 which obtains information regarding the physical environment surrounding the vehicle such as lane lines, obstacles, and etc., see [0049]-[0053] & [0061]+);
computing, based at least on the sensor data, a first vector representing, from a first side of the driving surface (the vehicle 100 includes a trajectory controller that computes an optimized trajectory (can be one or more paths, lines, curves or a combination thereof), see [0062]. The vehicle is currently in the lane segment 406A and is on its way to the destination at the lane segment 401, see [0083]+), one or more first probabilities that the machine is located within the one or more lanes (the vehicle locates at a lane segment with ID 1 probability, see [0095]+); and
computing, based at least on the sensor data, a second vector representing a second lane of the driving surface different from the first side of the driving surface, one or more second probabilities that the machine is located within the one or more lanes (second lane segment 404B with the ID 4, 5, 6, & 7, see [0085]+);
localizing, based at least on the first vector and the second vector, the machine to a lane of the one or more lanes (A connectivity graph converted into a model. Each vertex be a GPS coordinate for a point where a routing decision can be made of a lane change location, see [0092]+); and
causing the machine to perform one or more operations based at least on the machine being in the lane (control the vehicle to traverse the lane level route, see [0103]+).
Wray fails to teach computing, based on the sensor data, a second vector from a second side of the driving surface of the vehicle.
Towal discloses an autonomous machine using a deep neural network for path detection (see the abstract). The machine obtains sensor data which represents a path geometries 202 which includes a path geometry 202A on the left side of the machine, and a path geometry 202E on the right side of the machine (as same as the 1st and 2nd vector of the 1st and 2nd driving surface of the vehicle), see [0095]-[0096].
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Wray by including computing vectors from both driving surface sides of the vehicle as taught by Towal. The combination of Wray and Towal is an adapted system for improving of controlling the vehicle.
With regard to claim 2, Wray teaches that the method of claim 1, wherein the one or more lanes include at least the lane located proximate to the first side of the driving surface and a second lane located proximate to the second side of the driving surface; the first vector includes a first element associated with the first lane followed by a second element associated with the second lane; and the second vector includes at least a first element associated with the second lane followed a second element associated with the first lane (a road 402 includes three lanes 404A, 404B & 404C. Each lane includes lane segments, and probability vector ID, see [0083]-[0085] Which meets the scope of the claim.).
With regard to claim 3, Wray teaches that the method of claim 2, wherein: the one or more first probabilities include at least a first probability associated with the first element of the first vector and a second probability associated with the second element of the first vector; and the one or more second probabilities include at least a third probability associated with the first element of the second vector and a fourth probability associated with the second element of the second vector (The lane segments includes probability IDs, see [0085]+).
With regard to claim 4, Wray teaches that the method of claim 1, further comprising: obtaining second sensor data generated using the one or more sensors of the machine, the second sensor data representative of the one or more lanes of the driving surface within the environment; determining, based at least on the second sensor data, a third vector by updating the one or more first probabilities to include one or more third probabilities and a fourth vector by updating the one or more second probabilities to include one or more fourth probabilities; and determining, based at least on the third vector and the fourth vector, a least one of the lane or a second lane of the one or more lanes for which the machine is navigating (a road 402 includes three lanes 404A, 404B & 404C with multiple probability vector ID, see [0083]-[0085] Which meets the scope of the claim.).
.
With regard to claim 5, Wray teaches that the method of claim 1, further comprising: determining that the machine switched from the lane to a second lane of the one or more lanes; determining, based at least on data indicating that the machine switched from the lane to the second lane, a third vector by updating the one or more first probabilities to include one or more third probabilities and a fourth vector by updating the one or more second probabilities to include one or more fourth probabilities; and determining, based at least on the third vector and the fourth vector, the second lane of the one or more lanes for which the machine is navigating (lane changing based on the probability selected, see [0030]+).
With regard to claim 6, Wray teaches that the method of claim 1, further comprising: determining, based at least on one or more machine learning models processing the sensor data, a first output indicating at least one of one or more lane boundaries or one or more road boundaries and a second output indicating one or more locations of the one or more lanes, wherein the determining the first vector and the second vector is based at least on the first output and the second output (the HD map data includes details regarding curbs, lane boundaries, and etc., see [0043]+).
With regard to claims 7 & 18, Wray discloses a system comprising: one or more processors to:
determine, based at least on sensor data obtained using one or more sensors of a machine, outputs indicating, driving surfaces, one or more first probabilities that the machine is located within one or more lanes (vehicle 100 includes a sensor system 136 which obtains information regarding the physical environment surrounding the vehicle such as lane lines, obstacles, and etc., see [0049]-[0053] & [0061]+) & the vehicle locates at a lane segment with ID 1 probability, see [0095]+); and
causing the machine to perform one or more operations based at least on the machine being in the lane (control the vehicle to traverse the lane level route, see [0103]+).
Wray fails to teach computing, based on the sensor data, a second vector from a second side of the driving surface of the vehicle.
Towal discloses an autonomous machine using a deep neural network for path detection (see the abstract). The machine obtains sensor data which represents a path geometries 202 which includes a path geometry 202A on the left side of the machine, and a path geometry 202E on the right side of the machine (as same as the 1st and 2nd vector of the 1st and 2nd driving surface of the vehicle), see [0095]-[0096].
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify Wray by including computing vectors from both driving surface sides of the vehicle as taught by Towal. The combination of Wray and Towal is an adapted system for improving of controlling the vehicle.
With regard to claim 8, Wray teaches that the system of claim 7, wherein the one or more processors are further to: determine, based at least on the first output and the second output, that the machine is located within a lane of the one or more lanes, wherein the machine is caused to perform the one or more operations based at least on the machine being located within the lane (vehicle 100 includes a sensor system 136 which obtains information regarding the physical environment surrounding the vehicle such as lane lines, obstacles, and etc., see [0049]-[0053] & [0061]+);
With regard to claims 9 & 19, Wray teaches that the system of claim 7, wherein: the one or more first probabilities indicated by the first output are indexed starting at a first lane of the one or more lanes that is located proximate to the first side of the driving surface; and the one or more second probabilities indicated by the second output are indexed starting at a second lane of the one or more lanes that is located proximate to the second side of the driving surface (a road 402 includes three lanes 404A, 404B & 404C with multiple probability vector ID, see [0083]-[0085]).
With regard to claim 10, Wray teaches that the system of claim 7, wherein: the one or more first probabilities include at least a first probability associated with a first lane of the one or more lanes followed by a second probability associated with a second lane of the one or more lanes; and the one or more second probabilities include at least a third probability associated with the second lane followed by a fourth probability associated with the first lane (a road 402 includes three lanes 404A, 404B & 404C with multiple probability vector ID, see [0083]-[0085]).
With regard to claims 11-12, Wray teaches that the road 402 includes three lanes 404A, 404B & 404C with multiple probability vector ID which are continuously calculated and updated, see [0125]-[0127]+ which meet the scope of claims.
With regard to claims 13-14, Wray teaches that the system of claim 7, wherein the one or more processors are further to: determine that the machine has switched lanes; and determine, based at least on the machine switching lanes, a third output by updating the one or more first probabilities to include one or more third probabilities and a fourth output by updating the one or more second probabilities to include one or more fourth probabilities (lane changing based on the probabilities selected, see [0030]+).
With regard to claim 15, Wray teaches that the system of claim 7, wherein the one or more processors are further to: determine, based at least on one or more machine learning models processing the sensor data, a third output indicating at least one of one or more lane boundaries or one or more road boundaries and a fourth output indicating one or more locations of the one or more lanes, wherein the determination of the first output and the second output is based at least on the third output and the fourth output (the HD map data includes details regarding curbs, lane boundaries, and etc., see [0043]+).
With regard to claim 16, Wray teaches that the system of claim 7, wherein the one or more processors are further to: determine, based at least on a map associated with an environment that includes the driving surface, a type of road associated with the driving surface, wherein the determination of the first output and the second output is further based at least on the type of road (the lane segment lengths can be varied based on speed on a road, rush hour, road type, and etc., see [0084]+).
With regard to claims 17 & 20, Wray teaches that the system of claim 7, wherein the system is comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing one or more simulation operations; a system for performing one or more digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing one or more deep learning operations; a system implemented using an edge device; a system implemented using a robot; a system for performing one or more generative AI operations; a system for performing operations using one or more large language models (LLMs); a system for performing operations using one or more vision language models (VLMs); a system for performing one or more conversational AI operations; a system for generating synthetic data; a system for presenting at least one of virtual reality content, augmented reality content, or mixed reality content; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources (see [0079]+).
Prior Arts Cited
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Silver (20200365016) discloses a system for detecting and responding to traffic redirection for autonomous vehicles (see the abstract).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NGA X NGUYEN whose telephone number is (571)272-5217. The examiner can normally be reached M-F 5:30AM - 2:30PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, JELANI SMITH can be reached at 571-270-3969. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
NGA X. NGUYEN
Examiner
Art Unit 3662
/NGA X NGUYEN/Primary Examiner, Art Unit 3662