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 .
Claim Objections
Claim 3 is objected to because of the following informalities: the abbreviated term “AV” in “AV map” should be written out completely.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION. —The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-25 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites both “a system for navigating a host vehicle” and “a navigation system of the host vehicle to determine a navigational change for the host vehicle”. It is unclear with respect to the present specification whether “a navigation system” is meant the same as “a system for navigating” or if it is different. This creates ambiguity regarding the proper interpretations of the claim. Therefore, for the purpose of examination, “a navigation system” has been interpreted as “a navigational response module”, according to the specification e.g. paragraph [0142].
Claims 2-25 are rejected under 35 U.S.C § 112(b) as being dependent upon an indefinite claim.
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 1-35 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Statutory Category – Yes
Claims 1-35 are directed to a system, method and a non-transitory computer-readable medium. Therefore, the claim falls within at least one of the four statutory categories. See MPEP 2106.03
Step 2A Prong I evaluation: Judicial Exception – Yes – Mental processes
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.
In this case independent claims 1, 26, and 31 are directed to an abstract idea without significantly more. Claim 1 recites:
A system for navigating a host vehicle relative to a road segment, the system comprising: at least one processor comprising circuitry and a memory, wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to: receive a captured image representative of at least a portion of the road segment; receive a planned drivable path based on one or more map sections associated with the road segment, wherein the drivable path is determined for navigating the host vehicle; generate an overlaid representation of the captured image with the planned drivable path; provide the overlaid representation to a trained network, wherein the trained network is configured to receive the overlaid representation as input and provide, based on the combination of the captured image and the planned drivable path, an output that includes an indication of whether the host vehicle drivable path represents a valid path along the road segment; and cause a navigation system of the host vehicle to determine a navigational change for the host vehicle based on the indication of whether the host vehicle drivable path represents a valid path along the road segment.
The Office submits that the foregoing bolded limitations constitute 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). For example, limitation “receive a captured image…”, “receive a planned drivable path…”, and “determine a navigational change for the host vehicle based on the indication of whether the host vehicle drivable path represents a valid path along the road segment”, all can be performed in human mind and fall under the category of mental process. Also, the limitation “generate an overlaid representation of the captured image with the planned drivable path” can be done by a human using a pen and a paper, which falls under the mental process which is a category of abstract idea. Further, the limitation “providing the overlaid representation to a trained network, wherein the trained network is configured to receive the overlaid representation as input”, is considered as a mental process and/or a mathematical concept. Term “a trained network” is recited in a high level of generality and could be an algorithm and/or an image processing method both of which fall under mathematical concept. Accordingly, the claim recites at least one abstract idea.
Step2A Prong II evaluation: Practical Application – No
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 idea 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.”
The Office submits that the foregoing underlined limitations recite additional elements that do not integrate the recited judicial exception into a practical application. The claim recites the additional element of a processor, circuitry and memory in limitation “one processor comprising circuitry and a memory, wherein the memory includes instructions that when executed by the circuitry”, are no more than a generic computer. As such, they are mere instructions to apply the exception using a computer.
Step 2B evaluation: Inventive Concept – No
In Step 2B of the 2019 PEG, the claim(s) 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.
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, the limitation “cause a navigation system of the host vehicle to” amounts to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the Office submits that these limitations are insignificant extra-solution activities.
Claims 26 and 31 recites limitations for a system and a non-transitory readable-computer medium that comprise the same abstract as claim 1. Therefore, claims 26 and 31 are also patent ineligible for the same reasons stated in the above for claim 1 rejection.
Dependent claims 2-25 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 that do not integrate the judicial exception into a practical application. Claims 2-15 and 20-25 recite more description about receiving the captured image, map sections, and the indication of whether the host vehicle drivable path represents a valid path along the road segment; which all can be performed mentally and falls under abstract idea. Further, claims 16-17 recites steps of determining the navigational change without positively reciting a controlling step for the vehicle, therefore, claims 16-17 are also falls under mental process. Therefore, dependent claims 2-25 are not patent eligible under the same rationale as provided for the rejection of claim 1. Claims 27-30 and 32-35 _depend from claims 26 and 31, respectively_ encompass similar limitation as recited in claims 2-25 and are not patent eligible under the same rationale as provided for the rejection of claim 2-25.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-6, 14-15, 19-21, 23-28, 31 are rejected under 35 U.S.C. 103 as being unpatentable over Finelt et al., US20210101590A1, hereinafter “Finelt”, in view of Arnicar et al., US20230077909, hereinafter Arnicar.
Regarding claims 1, 24, 26 and 31, Finelt et al., US20210101590A1, discloses generating a trajectory to navigate a host vehicle based on identifying features along the map associated with the surrounding environment and Finelt teaches:
A system, a method and a non-transitory computer-readable medium for navigating a host vehicle relative to a road segment (Abstract, [0221]),
the system comprising: at least one processor comprising circuitry and a memory (claim 27), wherein the memory includes instructions that when executed by the circuitry ([0007], [0089])
cause the at least one processor to: receive a captured image representative of at least a portion of the road segment ([0005], “receive, from a camera, one or more images representative of an environment of the host vehicle;”)
Finelt also suggests validating the traveling course of the vehicle (for example according to paragraphs [0288], [0408]-[0412], [0423], [0425], [0429]) and although Finelt teaches:
receive a planned drivable path based on one or more map sections associated with the road segment, wherein the drivable path is determined for navigating the host vehicle ([0285], “the trajectory of vehicle 2305 may be determined by a processor provided aboard vehicle 2305 and transmitted to server 2330”, [0448], “ if the target trajectory is not consistent with the identified road segments (e.g., if the received spline suggests that the host vehicle is to navigate onto a curb or other invalid region), the processor may generate a planned trajectory for the host vehicle, based at least in part on the target trajectory, such that the planned trajectory is made to extend along at least a some of the identified road segments and cause at least one adjustment of a navigational actuator of the host vehicle to cause the host vehicle to navigate relative to the planned trajectory.” __Examiner’s Note: according to at least paragraph [0448], the processor uses the received target trajectory (reads on planned drivable path in the claim), and further may generate a planned trajectory based on the received target trajectory. Accordingly, the disclosure of Finelt meets the recited imitation);
generate an overlaid representation of the captured image with the planned drivable path __wherein the overlaid representation is in the form of a generated image representation as recited in claim 24 __([0119], “a FOV (such as FOV 204) associated with image capture device 124 may overlap partially or fully with a FOV (such as FOV 202) associated with image capture device 122 and a FOV (such as FOV 206) associated with image capture device 126.”, [0120], [0165], “processing unit 110 may create a projection of the detected segments from the image plane onto the real-world plane.”, Fig. 48);
provide the overlaid representation to a trained network, wherein the trained network is configured to receive the overlaid representation as input (Figs. 9A-9C, [0031], [0189]-[0190], [0193]-[0194], [0200], “the method of estimating a future path ahead of a current location of a vehicle can include: obtaining an image of an environment ahead of a current arbitrary location of a vehicle navigating a road (block 1110). A system that was trained to estimate a future path on a first plurality of images of environments ahead of vehicles navigating roads can be obtained (block 1120). In some embodiments, the trained system may include a network, such as a neural network.”, [0201]-[0202], “”, [0413]) and
provide, based on the combination of the captured image and the planned drivable path, an output that includes an indication of whether the host vehicle drivable path represents a valid path along the road segment ([0403], [0410], [0411]-[0412], [0423], [0429], [0431]-[0432]); and
cause a navigation system of the host vehicle to determine a navigational change for the host vehicle based on the indication of whether the host vehicle drivable path represents a valid path along the road segment ([0432], “a directional indicator/distance estimate pair may refer to a location where no navigable road segment exists or where the host vehicle cannot validly travel along a road segment at the specified distance. […] Through image analysis, the navigational processors may determine that the received directional indicator/distance estimate pair corresponds to a location that would cause the host vehicle to drive on the curb. […] In such cases, the navigational processors may generate a planned trajectory for the host vehicle that traverses the navigable path of the road segment recognized from the image analysis.”, [0446]-[0448]).
Furthermore, although Finelt implicitly teaches processing the image from the projection of road segments onto the environment data, however, for the purpose of compact prosecution, Examiner further relied on teaching of Arnicar that more explicitly suggests:
generate an overlaid representation of the captured image with the planned drivable path __wherein the overlaid representation is in the form of a generated image representation, as recited in claim 24__ ([0013], “The map data may be projected into image data representing at least the road network from a perspective of a vehicle,”, [0014], “By projecting map data reference marks into actual image data captured by a vehicle (e.g., overlaying semantic information from the map into an image frame), map data can be validated “off-vehicle” in a controlled environment.”, [0038], [0075]) and
provide the overlaid representation to a trained network, wherein the trained network is configured to receive the overlaid representation as input ([0012], "Additionally, data (e.g., sensor data of the environment) that may be necessary to confirm the validity or correctness of the map data may still need to be captured to verify the map data is accurate.,", [0013], "The map data may be projected into image data representing at least the road network from a perspective of a vehicle, and the position of the reference marks relative to the features of the road network may be compared. If the position of the reference marks do not correspond with the actual location of the road network features, then the reference marks may be corrected/adjusted.", [0014], "By projecting map data reference marks into actual image data captured by a vehicle (e.g., overlaying semantic information from the map into an image frame), map data can be validated “off-vehicle” in a controlled environment.", Fig 2B, and [0026], “A cartographer 120 (e.g., a human cartographer, a machine-learned model, a computing device that is automated to generate map data, etc.) may receive the top-down scene data 110 and use it to generate map data 122. The map data 122 may comprise semantic map data.”, __Examiner’s Note: map data according to paragraph [0013], and [0014], comprises the projection of semantic information from the map into the image captured from the environment__, also see [0032], [0033], [0035], [0045], [0047]).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—, in view Arnicar, which teaches techniques for generating and validating map data that a vehicle can use to traverse an environment. Specifically, Arnicar suggests overlaying semantic map data into actual image data to validate routes and confirming that the drivable surface is valid. Thus, a skilled artisan would have been motivated to combine Finelt in view of Arnicar to arrive at the claimed limitations, driven by the goal of improving the accuracy of navigating a vehicle through planned trajectories relative to the real-time state of the road and surrounding environment.
Regarding claim 2, Finelt teaches the system of claim 1, wherein the one or more map sections are part of a sparse map ([0277], [0410]).
Regarding claim 3, Finelt teaches the system of claim 1, wherein the one or more map sections are part of an AV map (e.g., [0217])
Regarding claim 4, Finelt teaches the system of claim 1, and Finelt teaches wherein the planned drivable path is a 3D spline (e.g., [0227]).
Regarding claims 5 and 27, Finelt in view of Arnicar teaches the system and method of claims 1 and 26, and Finelt teaches wherein the captured image is indicative of a real-world location of the host vehicle drivable path as viewed from a vantage point of a camera that acquired the captured image ([0003], “an autonomous vehicle may also need to identify its location within a particular roadway (e.g., a specific lane within a multi-lane road)”, [0093], [0111], [0137], [0414]), “one or more images representative of an environment of the host vehicle. As noted above, such images, e.g., may be captured by one or more cameras onboard a host vehicle.”.
Regarding claims 6 and 28, Finelt in view of Arnicar teaches the system and method of claims 1 and 26, and Finelt teaches wherein the captured image is indicative of a real-world location of the host vehicle drivable path as viewed from a simulated vantage point higher above a road surface associated with the road segment than a camera that acquired the captured image ([0100]-[0101]).
Regarding claims 11 and 34, Finelt in view of Arnicar teaches the system and non-transitory medium of claims 1 and 31, however, Finelt doesn’t explicitly teaches wherein the indication represents an invalid path if the host vehicle drivable path extends off a road pathway of the road segment represented in the overlaid representation.
Arnicar teaches wherein the indication represents an invalid path if the host vehicle drivable path extends off a road pathway of the road segment represented in the overlaid representation (at least Fig. 5).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar, and further modify Finelt to include the step of determining an invalid path if if the host vehicle drivable path extends off a road pathway of the road segment represented in the overlaid representation, as taught by Arnicar, with a reasonable expectation of success, with the motivation of increasing the reliability of the navigation system by determining if the planned path is drivable.
Regarding claim 14, Finelt in view of Arnicar teaches the system of claim1, and Finelt teaches wherein the indication represents an invalid path if the host vehicle drivable path intersects a longitudinal lane marking represented in the overlaid representation (Finelt, [0151], “monocular image analysis module 402 may include instructions for detecting a set of features within the set of images, such as lane markings,”, [0155], “By performing the analysis, processing unit 110 may detect a set of features within the set of images, such as lane markings,”, [0164], [0197], “one or more regions that the navigational processor(s) determine are not navigable (e.g., parked car locations, curbs, walls, etc.) based on analysis of the captured images.”, [0403], “landmarks may include one or more traffic signs, arrow markings, lane markings, dashed lane markings,”, [0406], “determine a planned trajectory based on numerous criteria or considerations. Just a few examples of such criteria or considerations may include identified free space ahead of the host vehicle, identified lane markings, identified road edges, ”, [0470], “This information, coupled with an expectation that the target vehicle will obey road markings and remain on the correct side of the centerline, may enable the navigation system to determine that no remedial action is required in the scenario of FIG. 48.”).
Regarding claim 15, Finelt in view of Arnicar teaches the system of claim 1, and Finelt teaches wherein the indication represents an invalid path if the host vehicle drivable path intersects with an edge of a road surface represented in the overlaid representation (Finelt, [0425] “one or more regions that the navigational processor(s) determine are not navigable (e.g., parked car locations, curbs, walls, etc.) based on analysis of the captured images”, [0432], __curb in Finelt’s disclosure reads on edge of a road__).
Regarding claim 19, Finelt in view of Arnicar teaches the system of claim 1, and Finelt teaches wherein the navigational change includes slowing or stopping the host vehicle ([0479], “a remedial action for the host vehicle in response to the oncoming target vehicle and the potential turn-across-path event. […] the remedial action may include braking of the host vehicle. For example, the host vehicle may reduce its speed or come to a stop”, [0486], “the remedial action for the host vehicle may include forgoing application of brakes of the host vehicle” “alternate actions may include reducing a speed of the host vehicle”)
Regarding claim 20, Finelt in view of Arnicar teaches the system of claim 1, and Finelt teaches wherein the navigational change includes determining a revised valid target drivable path based on one or more road topography features represented in the captured image and controlling the navigation of the host vehicle to follow the revised target drivable path (Finelt [0421]-[0422], “suggesting a heading direction different from a current heading direction of the host vehicle may provide valuable information for generating a planned trajectory for the host vehicle, as it may indicate a directional change for the host vehicle correlated to one or more road features that may be observed in the captured images.”, [0406]-[0416], [0425]-[0426], [0432], [0438], see also [0145], [0151]-[0153])
Regarding claim 21, Finelt in view of Arnicar teaches the system of claim 1, and Finelt teaches wherein the navigational change includes navigating without reliance upon the host vehicle drivable path (Finelt [0261], “vehicles may modify their actual, reconstructed trajectories and submit (e.g., recommend) to the server the modified actual trajectories.”).
Regarding claim 23, Finelt in view of Arnicar teaches the system of claim 1, and Finelt teaches wherein the memory includes instructions that when executed by the circuitry cause the at least one processor to: send map change information to a map server in response to an indication that the host vehicle drivable path represents an invalid path along the road segment ([0257], “the server may generate or update an already generated sparse map 1900 to include trajectories that may be more suitable or safer for autonomous driving under the detected environmental conditions.”, [0297], [0390], “”, [0449], “ the observed disparity between a received spline and observed road segments identified in the captured images may be used to prompt an upload of collected visual and trajectory information and an update to the stored sparse map.”).
Regarding claim 25, Finelt in view of Arnicar teaches the system of claim 1, and Finelt teaches wherein the trained network includes a neural network ([0195], [0200], “the trained system may include a network, such as a neural network.”, [0213]).
Claim(s) 7-8, and 29-30 are rejected under 35 U.S.C. 103 as being unpatentable over Finelt in view of Arnicar, further in view of Danford, US 20210405642 A1, hereinafter “Danford”
Regarding claims 7-8, 29-30, Finelt in view of Arnicar tecahes the system and method of claims 1 and 26, and although Finelt teaches a confidence level (at least see paragraph [0213]), however, Finelt doesn’t explicitly disclose wherein the indication of whether the host vehicle drivable path represents a valid path along the road segment includes a confidence score, and wherein the host vehicle drivable path represents an invalid path if the confidence score is less than a predetermined threshold.
Danford teaches:
wherein the indication of whether the host vehicle drivable path represents a valid path along the road segment includes a confidence score ([0018], “secondary compute system determines the planned trajectory as failing to satisfy the confidence threshold, the simplified secondary compute system may proceed in altering the numerical measurement parameters [] associated with the planned trajectory to generate an altered planned trajectory.”, “On the other hand, when the simplified secondary compute system determines the planned trajectory as satisfying the confidence threshold, the simplified secondary compute system may forgo altering the numerical measurement parameters and/or kinematic measurement parameters associated with the planned trajectory, and, instead, simply instruct the vehicle to execute the initially planned trajectory.”
wherein the host vehicle drivable path represents an invalid path if the confidence score is less than a predetermined threshold (e.g. [0018], “secondary compute system determines the planned trajectory as failing to satisfy the confidence threshold, [] generate an altered planned trajectory.”, [0036], “determine whether the planned trajectory generated by the robust primary compute system 202 satisfies a confidence threshold.”, [0040],-[0045], “to validate the planned trajectory generated by the robust primary compute system 202 satisfies the confidence threshold.”, __Examiner’s Note: according to Danford’s disclosure, if confidence score satisfices a confidence score threshold, the planned trajectory is valid. Satisfying a confidence score threshold reads on if the confidence store is higher than a predetermined which shows the planned trajectory is valid, and accordingly if it is less than a predetermined threshold, the path is determined to be invalid. __).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar. Furthermore, it would have been obvious to modify Finelt to use a predetermined confidence score threshold to determine whether the planned path is invalid, with a reasonable expectation of success. This modification is motivated by the desire to provide a quantitative measure of the neural network's certainty regarding the validity of a planned path. This improves the system's accuracy and reliability by detecting uncertain predictions and avoiding sole reliance on the predicted outcome.
Claim(s) 9-10, and 32-33 are rejected under 35 U.S.C. 103 as being unpatentable over Finelt, in view of Arnicar, further in view of Behrendt et al., US 20210004966 A1, hereinafter “Berhrendt”.
Regarding claims 9 and 32, Finelt in view of Arnicar teaches the system and non-transitory medium of claims 1 and 31, and although Finelt implicitly teaches wherein the indication of whether the host vehicle drivable path represents a valid path along the road segment includes a difference indicator between the host vehicle drivable path and a target drivable path determined by a trained network based on one or more road topography features represented in the overlaid representation (at least [0218], “correlate or match the road feature with the stored signature based on an image (or a digital signal generated by a sensor, if the stored signature is not based on an image and/or includes other data) of the road feature that is captured by a camera onboard a vehicle traveling along the same road segment at a subsequent time.” [0255], [0398], “vehicle 200 may measure a profile associated with one or more parameters associated with that road segment. If the measured profile can be correlated/matched with a predetermined profile that plots the parameter variation with respect to position along the road segment, then the measured and predetermined profiles may be used by vehicle 200 (e.g., by overlaying corresponding sections of the measured and predetermined profiles) in order to determine a current position along the road segment and, therefore, a current position relative to target trajectory 3600 for the road segment.” Or [0445], “The derived directional indicators and distance estimates may be compared to one or more captured images, and the navigational processor(s) may determine whether navigable road segments exist that are consistent with and available for performing a maneuver suggested by the derived directional indicators and distance estimates.”).
Behrendt more explicitly teaches wherein the indication of whether the host vehicle drivable path represents a valid path along the road segment includes a difference indicator between the host vehicle drivable path and a target drivable path determined by a trained network based on one or more road topography features represented in the overlaid representation. ([0087]-[0088], “using a deviation of the observed trajectory from the at least one possible trajectory”, [0090], “the assessment of an observed trajectory-traffic environment combination in a captured traffic environment, a difference of a possible trajectory of a transport road user from an observed trajectory is calculated using a metric.”, [0099]-[0111] __ Examiner’s Note: metric in Behrendt’s disclosure read on difference indicator in the claim__)
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar, and uses difference between the planned path and the target path determined by a trained network, as an indication whether the planned path is valid, as implicitly taught by Finelt and more explicitly taught by Behrendt, with a reasonable expectation of success, with the motivation of increasing the reliability of the navigation system by determining if the planned and target path are match.
Regarding claims 10 and 33, modified Finelt teaches the system and non-transitory medium of claims 9 and 32, however it doesn’t explicitly teach wherein the host vehicle drivable path represents an invalid path if the difference indicator is greater than a predetermined threshold
Behrendt teaches wherein the host vehicle drivable path represents an invalid path if the difference indicator is greater than a predetermined threshold (Behrendt 0091], “all trajectories are explicitly assessed using a metric. The recommendation service will then seek to implicitly minimize this metric, corresponding to a similarity metric, by means of the assessments.”, [0075], [0108], __ Note: determining one possible trajectory based on minimizing the metric (which indicates the variation/difference between observed and possible trajectory) reads on the claimed feature of representing invalid path if the difference indicator (reads on metric in Behrendt’s disclosure) being greatest than a predetermined threshold).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar, and uses difference between the planned path and the target path determined by a trained network, as an indication whether the planned path is valid and compare that indication with a predetermined threshold, as taught by Behrendt, with a reasonable expectation of success, with the motivation of increasing the reliability of the navigation system by determining if the planned and target path are match.
Claim(s) 12-13, and 35 are rejected under 35 U.S.C. 103 as being unpatentable over Finelt, in view of Arnicar, or in alternative rejection, Claim(s) 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Finelt, in view of Arnicar further in view of Ferguson US 9145139 B2, hereinafter “Ferguson”.
Regarding claims 12 and 35, modified Finelt teaches the system and non-transitory medium of claims 1 and 31, and Finelt teaches wherein the indication represents an invalid path if the host vehicle drivable path intersects with an object represented in the overlaid representation (Finelt [0082], “”, [0142]-[0145], [0151]-[0154], [0158]-[0164]]
Also, in alternative rejection, Ferguson teaches wherein the indication represents an invalid path if the host vehicle drivable path intersects with an object represented in the overlaid representation (at least Figs. 3A and 3B and associated paragraphs).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar, to indicate an invalid path where an object is present in the host vehicle path as taught also by Finelt. Alternatively, this modification could be made in view of Ferguson. Both combinations provide a reasonable expectation of success and share the same motivation: increasing safety and improving the accuracy and reliability of the navigation system by flagging the vehicle's drivable path as invalid if an object is present.
Regarding claim 13, modified Finelt teaches the system of claim 12, and Finelt teaches wherein the object includes a parked vehicle, a pedestrian, or a stationary object on a road surface associated with the road segment and a barrier (Finelt, [0143], [0151], “detecting a set of features within the set of images, such as lane markings, vehicles, pedestrians, road signs, highway exit ramps, traffic lights, hazardous objects, and any other feature associated with an environment of a vehicle.”)
Also, in alternative rejection, Ferguson teaches wherein the object includes a parked vehicle, a pedestrian, or a stationary object on a road surface associated with the road segment and a barrier (at least Col 3 last paragraph, and Col 4 first paragraph, “any obstacles (e.g., road flares, cones, other vehicles, etc.) that might interfere with the travel of the vehicle may be important to the vehicle,”).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar, to indicate an invalid path where an object (including pedestrians, road signs/stationary object, hazardous objects/obstacle) is present in the host vehicle path as taught also by Finelt. Alternatively, this modification could be made in view of Ferguson. Both combinations provide a reasonable expectation of success and share the same motivation: increasing safety and improving the accuracy and reliability of the navigation system by flagging the vehicle's drivable path as invalid if an object is present.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Finelt, in view of Arnicar, further in view of Umeda US 20200298886 A1, herein after “Umeda”.
Regarding claim 16, modified Finelt teaches the system of claim 1, however, it doesn’t explicitly teach wherein the navigational change includes exiting an autonomous vehicle driving mode.
Nevertheless, Umeda teaches wherein the navigational change includes exiting an autonomous vehicle driving mode (Umeda et al., US 20200298886 A1 [0049] “to avoid an obstacle in the route 80, the driving mode of the vehicle 50C has been just switched from the autonomous driving mode to the manual driving mode temporarily, or another case. In such a case, the boarding staff 51 desirably, for example, avoids the obstacle in the route 80 in the manual driving mode and then quickly switches into the autonomous driving mode.”).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar, to further modify Finelt to include feature of exiting an autonomous mode as a navigational response in the event of detecting an invalid path, as taught by Umeda, with a reasonable expectation of success, with the motivation of increasing safety of autonomous driving.
Claims 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Arnicar, further in view of Umeda, further in view of Guo US 11702110 B2, hereinafter “Guo”.
Regarding claim 17, modified Finelt teaches the system of claim 16, however, it doesn’t explicitly teach wherein the navigational change further includes re-entering the autonomous vehicle driving mode after a subsequent determination that the host vehicle drivable path represents a valid path along the road segment.
Guo teaches wherein the navigational change further includes re-entering the autonomous vehicle driving mode after a subsequent determination that the host vehicle drivable path represents a valid path along the road segment (Col 29 second paragraph, “at decision block 1628 it is determined if the autonomous driving system is ready for Level 4 or Level 5. If the autonomous driving system is ready for Level 4 or Level 5 at decision block 1628 (YES), process 1600 proceeds to block 1636 where processor 340 sets the autonomous driving system to ready and checks the autonomous driving mode transition safety conditions.”).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar, and further in view of Umeda that teaches exiting the autonomous mode temporarily to avoid an obstacle (i.e. when determining the path is invalid), and to further modify Finelt to include feature of re-entering an autonomous mode as a navigational response when determining that the vehicle is ready for level 4 or level 5 (reads on determination that the host vehicle drivable path is valid for autonomous driving) , as taught by Guo, with a reasonable expectation of success, with the motivation of increasing safety and reliability of autonomous driving.
Regarding claim 18, modified Finelt teaches the system of claim 17, however, it doesn’t explicitly teach wherein re-entering the autonomous vehicle driving mode is delayed until a number of subsequent determinations that the host vehicle drivable path represents a valid path along the road segment meets or exceeds a predetermined threshold
Guo teaches wherein re-entering the autonomous vehicle driving mode is delayed until a number of subsequent determinations that the host vehicle drivable path represents a valid path along the road segment meets or exceeds a predetermined threshold (at least Col 20 Lines 41-52, and Col 25 Lines 37-42).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar, and further in view of Umeda that teaches exiting the autonomous mode temporarily to avoid an obstacle (i.e. when determining the path is invalid), and to further modify Finelt to include feature of re-entering an autonomous mode as a navigational response when determining that the vehicle is ready for level 4 or level 5 (reads on determination that the host vehicle drivable path is valid for autonomous driving) , as taught by Guo, and also delay re-entering the autonomous vehicle until multiple estimates of whether autonomous driving is appropriate is made for a certain time, with a reasonable expectation of success, with the motivation of increasing safety and reliability of autonomous driving.
Claim(s) 22 is rejected under 35 U.S.C. 103 as being unpatentable over Finelt, in view of Arnicar, further in view of Gier US 20210129834 A1, hereinafter “Gier”.
Regarding claim 22, modified Finelt teaches the system of claim 1, however it doesn’t explicitly teach wherein the navigational change includes navigating without reliance upon the one or more map sections.
Gier teaches wherein the navigational change includes navigating without reliance upon the one or more map sections ([0041], “the vehicle 104 can determine the partial lane expansion action and the candidate trajectory 212 as the target trajectory. For example, the vehicle 104 can, based on the sensor data, determine a width required by the vehicle 104 to pass the object 116.”).
It would have been obvious to a person of ordinary skill in the art prior to the effective filing date to modify the systems and methods for navigating a host vehicle taught by Finelt—which discloses validating a target path or traveling course—in view of Arnicar, to further modify Finelt to include the navigational response such as determining a candidate trajectory based on sensor data (i.e. without reliance upon the one or more map sections), as taught by Gier, with a reasonable expectation of success, with the motivation of increasing the reliability of the navigating system in sending a proper navigational change when the vehicle encounters an unexpected obstacle in the host vehicle's environment.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAJAR HASSANIARDEKANI whose telephone number is (571)272-1448. The examiner can normally be reached Monday thru Friday 8 am-5 pm ET.
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, Erin Piateski can be reached at 5712707429. 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.
/H.H./Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669
Prosecution Insights