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 .
Summary
This communication is a First Office Action Non-Final Rejection on the merits.
Claims 1 – 20 are currently pending and considered below.
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 [AltContent: connector]abstract idea without significantly more.
[AltContent: connector]101 Analysis – Step 1
[AltContent: connector]Claim 1 is directed to a computer that analyzes the environment of the ego vehicle and determine relevance scores for objects in the environment based on the position of the objects in the field. 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 in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
A computer comprising a processor and a memory, the memory storing instructions executable by the processor to:
generate a potential field covering an environment surrounding an ego vehicle and centered on the ego vehicle, the potential field indicating relevance to the ego vehicle; and
determine a relevance score for an object in the environment according to a position of the object in the potential field.
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 limitations in the human mind. For example, “generating…,” and “determining …,” in the context of this claim encompasses a person 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 in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, 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, there is no the additional limitations beyond the above-noted abstract idea that integrate the abstract idea into a practical application.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, there is no the additional element that integrate the abstract idea into a practical application. Since there is no additional elements, there is no analysis needed for significantly more or if additional elements are well-known, routine and conventional activities.
Dependent claims 2 – 16 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of 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 – 16 are not patent eligible under the same rationale as provided for in the rejection of claim 1.
Therefore, claims 1 – 16 are ineligible under 35 U.S.C. §101.
Claims 17 – 20 recites same or substantially similar limitations as claims 1 – 16. Therefore claims 17 – 20 are rejected under same rationales.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 – 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Tao et al. (Hereinafter Tao) (US 10928820 B1).
As per claim 1, Tao teaches the limitations of:
a computer comprising a processor and a memory, the memory storing instructions executable by the processor (See at least column 6 line 9 – 13; Perception module 302 may include a computer vision system or functionalities of a computer vision system to process and analyze images captured by one or more cameras in order to identify objects and/or features in the environment of autonomous vehicle.) to:
generate a potential field covering an environment surrounding an ego vehicle and centered on the ego vehicle, the potential field indicating relevance to the ego vehicle (See at least column 5 line 61 – column 6 line 22; Based on the sensor data provided by sensor system 115 and localization information obtained by localization module 301, a perception of the surrounding environment is determined by perception module 302. The perception information may represent what an ordinary driver would perceive surrounding a vehicle in which the driver is driving. The perception can include the lane configuration, traffic light signals, a relative position of another vehicle, a pedestrian, a building, crosswalk, or other traffic related signs (e.g., stop signs, yield signs), etc., for example, in a form of an object. The lane configuration includes information describing a lane or lanes, such as, for example, a shape of the lane (e.g., straight or curvature), a width of the lane, how many lanes in a road, one-way or two-way lane, merging or splitting lanes, exiting lane, etc. Perception module 302 may include a computer vision system or functionalities of a computer vision system to process and analyze images captured by one or more cameras in order to identify objects and/or features in the environment of autonomous vehicle. The objects can include traffic signals, road way boundaries, other vehicles, pedestrians, and/or other obstacles, etc. The computer vision system may use an object recognition algorithm, video tracking, and other computer vision techniques. In some embodiments, the computer vision system can map an environment, track objects, and estimate the speed of objects, etc. Perception module 302 can also detect objects based on other sensors data provided by other sensors such as a radar and/or LIDAR.); and
determine a relevance score for an object in the environment according to a position of the object in the potential field (See at least abstract, and column 6 line 39 – 46; a process is performed during controlling Autonomous Driving Vehicle (ADV). A plurality of point confidence scores are determined, each defining a reliability of a corresponding point on a trajectory of a moving obstacle. At least one of the point confidence scores is determined based on a) an overall trajectory confidence score, and b) at least one environmental factor of the obstacle. The ADV is controlled based on the trajectory of the moving obstacle and at least one of the plurality of point confidence scores. … prediction module generates a predicted trajectory of an obstacle, for example, a vehicle other than the ADV, a pedestrian, or a cyclist, that predicts a path of the moving obstacle, at least in an area that is deemed relevant to a current path of the ADV. The predicted trajectory can be generated based the current status of the moving obstacle (e.g., speed, location, heading, acceleration, or a type of the moving obstacle), map data, and traffic rules. The Examiner construes that based on specification particularly in paragraph 60 and 62, the relevance score is closely tied to the trajectory/heading of object and confidence score of the trajectory of object.); .
As per claim 2, Tao teaches the limitations of:
wherein the instructions further include instructions to operate the ego vehicle based on the relevance score (See at least column 10 line 18 – 41).
As per claim 3, Tao teaches the limitations of:
wherein the instructions further include instructions to generate the potential field based on a speed at which the ego vehicle is traveling through the environment (See at least column 3 line 30 – 52).
As per claim 4, Tao teaches the limitations of:
wherein the instructions further include instructions to determine a longitudinal reference distance extending longitudinally from the ego vehicle based on the speed, and generate the potential field based on the longitudinal reference distance (See at least column 6 line 59 – column 7 line 31).
As per claim 5, Tao teaches the limitations of:
wherein the instructions further include instructions to generate the potential field based on a layout of a road on which the ego vehicle is traveling (See at least column 5 line 61 – column 6 line 8).
As per claim 6, Tao teaches the limitations of:
wherein the instructions further include instructions to determine a lateral reference distance extending laterally from the ego vehicle based on the layout of the road, and generate the potential field based on the lateral reference distance (See at least column 7 line 8 – 28).
As per claim 7, Tao teaches the limitations of:
wherein the lateral reference distance is a left lateral reference distance extending left from the ego vehicle, and the instructions further include instructions to determine a right lateral reference distance extending laterally right from the ego vehicle based on the layout of the road, and generate the potential field based on the left lateral distance and the right lateral reference distance, the right lateral reference distance being different than the left lateral reference distance (See at least column 5 line 61 – column 6 line 8).
As per claim 8, Tao teaches the limitations of:
wherein the layout of the road includes a lane line of the road, and the instructions further include instructions to generate the potential field based on the lane line (See at least column 5 line 61 – column 6 line 8).
As per claim 9, Tao teaches the limitations of:
wherein the layout of the road includes an upcoming intersection in a forward direction from the ego vehicle, and the instructions further include instructions to generate the potential field based on the upcoming intersection (See at least column 6 line 23 – 38).
As per claim 10, Tao teaches the limitations of:
wherein the instructions further include instructions to generate the potential field based on a position of a target vehicle (See at least column 6 line 9 – 22).
As per claim 11, Tao teaches the limitations of:
wherein the instructions further include instructions to determine a longitudinal reference distance extending longitudinally from the ego vehicle based on the position of the target vehicle, and generate the potential field based on the longitudinal reference distance (See at least column 7 line 17 – 31 and column 10 line 32 – 41).
As per claim 12, Tao teaches the limitations of: wherein the target vehicle is a leading vehicle traveling ahead of the ego vehicle (See at least column 6 line 22 – 38).
As per claim 13, Tao teaches the limitations of:
wherein the potential field is defined relative to a Frenet frame following a lane of travel of the ego vehicle (See at least figure 8).
As per claim 14, Tao teaches the limitations of:
wherein the potential field is continuously differentiable across the environment (See at least column 4 line 51 – 64).
As per claim 15, Tao teaches the limitations of:
wherein the instructions further include instructions to determine the relevance score for the object based on a heading of the object (See at least abstract, and column 6 line 39 – 46).
As per claim 16, Tao teaches the limitations of:
wherein the instructions further include instructions to determine the relevance score based on an angle between the heading of the object and a gradient of the potential field at the position of the object (See at least column 7 line 32 – 41).
Regarding claims 17 – 20:
Claims 17 – 20 are rejected using the same rationale, mutatis mutandis, applied to claims 1 – 16 above, respectively.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Eggert et al. (US 2020/0231149 A1) discloses method for assisting a driver, driver assistance system and vehicle including such driver assistance system.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IG T AN whose telephone number is (571)270-5110. The examiner can normally be reached M - F: 10:00AM- 4:00PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Aniss Chad can be reached at (571) 270-3832. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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IG T AN
Primary Examiner
Art Unit 3662
/IG T AN/Primary Examiner, Art Unit 3662