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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/03/2026 has been entered.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 04/03/2026 is/are being considered by the Examiner.
Response to Arguments
Applicant's arguments filed 04/03/2026 with respect to previously rejected claim limitations have been fully considered but they are not persuasive.
On page 7 of the Remarks, Applicant argues that primary reference Ingram does not teach the previously claimed “determining, based on the current scenario, a level of computational resources appropriate for the current scenario”. Specifically, Applicant argues that Ingram’s teaching of managing sensor emission power is distinct from determining a level of computational resources as described in the Specification in the present application. However this is not persuasive because paragraph [0020] of the present published application lists battery power as a computational resource and paragraphs [0029]-[0030] of Ingram specify how determining vehicle scenarios can allow for increasing or decreasing an amount power consumption via the power configuration for radar sensors while paragraph [0032] does the same for LIDAR. Therefore, one of ordinary skill in the art would recognize a direct analogy between determining a power configuration (which is related to power consumption per Ingram) based on a vehicle scenario and determining a level of computational resources (i.e. battery power) needed based on a vehicle scenario and adjusting a sensor accordingly.
On page 8 of the Remarks, Applicant then argues that the Examiner has not pointed out how Ingram teaches previous claims 4, 13, and 18, specifically “wherein the level of computational resources appropriate for the current scenario is determined based at least in part on the current vehicle status", which has effectively been amended into the independent claims. However, this is not persuasive because paragraph [0066] of Ingram, previously cited in the Final action, specifically notes that the operating context of a vehicle, which is ultimately used to decide the power configuration, is determined by multiple factors such as vehicle speed. Paragraph [0103] of the present published application indicates that vehicle status can be an indication of high vehicle speed and therefore Ingram teaches a vehicle status consistent with the present application. Furthermore, as shown in the rejections for the independent claims, the operating context which includes a vehicle status per paragraph [0066] of Ingram then leads to the level of computational resources to be determined as shown in Ingram Figure 2.
Applicant’s arguments with respect to claim(s) 1, 10, and 15 regarding the newly added limitations have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claim(s) 1, 5, 10, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ingram et al, U.S. Publication No. 2021/0088647 in view of Halder, U.S. Publication No. 2019/0310654.
Regarding claim 1, Ingram teaches a vehicle (see Ingram Figure 1 and paragraph [0034]), comprising:
at least one computer-readable medium storing computer-executable instructions; at least one processor communicatively coupled to at least one sensor and configured to execute the computer executable instructions, the execution carrying out operations (see Figure 1, processor 152 and memory 154 and paragraph [0057]) comprising:
obtaining, from the at least one sensor (see Figure 1, lidar sensor 120 and radar sensor 130), information representative of an environment surrounding the vehicle (see Figure 2, sensor data 202 and 204 and paragraph [0061]);
determining, based on the information representative of the environment of the vehicle, a scenario type corresponding to a current scenario of the environment of the vehicle (see Figure 2, steps 210 to 220 and paragraph [0066]. The scenario type could be “roadway type” or “traffic density” which is consistent with the examples given in paragraph [0107] of the published application);
determining, based on the scenario type and a status of the vehicle (see paragraph [0066] which includes speed of the vehicle when determining an operating context. The full operating context therefore could include “roadway type”/ “traffic density” and “speed of the vehicle”), a level of computational resources appropriate for the current scenario (see Figure 2, step 230 and paragraphs [0068] and [0078]. As indicated above, paragraph [0020] of the present published application lists battery power as a “computational resource” and paragraphs [0029]-[0030] and [0032] of Ingram show how power consumption is controlled by the power configuration of Figure 2); and
adjusting at least one parameter associated with the at least one sensor based on the level of computational resources (see Figure 1, step 240 and paragraphs [0068] and [0078]).
Ingram does not expressively teach determining, based predicted operations of the vehicle, [the] scenario type.
However, Halder in a similar invention in the same field of endeavor teaches a system comprising a vehicle (see Halder Figure 1A) configured for obtaining, from the at least one sensor, information representative of an environment surrounding the vehicle (see Figure 1A, sensors 110 and [0056]); determining a scenario type corresponding to a current scenario of the environment of the vehicle (see Figure 1, AVMS 122 and paragraph [0058] and [0060]); determining, based on the scenario type, a level of computational resources appropriate for the current scenario (see paragraph [0126], “For example, in certain scenarios, more detailed data (which translates to more detailed information about the ego vehicle's environment) can be used to make decisions regarding actions to be performed by autonomous vehicle 120. In some other scenarios, the amount of sensor data received from a sensor may be reduced for more efficient use of the sensor (e.g., to save power used by the sensor) without overwhelming autonomous vehicle management system 122 with unnecessary data. All this is done without comprising any safety considerations. The overall safety of autonomous operations performed by autonomous vehicle 120 is improved while making efficient use of memory/processing resources and of the sensors”); and adjusting at least one parameter associated with the at least one sensor based on the level of computational resources (see Figure 11, step 1102 and paragraph [0119]) as taught in Ingram further comprising
determining, based predicted operations of the vehicle, [the] scenario type (see paragraph [0112], “Example #1: Autonomous vehicle management system 122 may have received information indicative of a particular goal for autonomous vehicle 120, and a change in sensor data is needed to safely facilitate this goal. For example, the particular goal could be a certain operation that is to be performed by autonomous vehicle 120, such as a left/right turn, change traffic lanes, perform a certain specialized task (e.g., digging), and the like. Autonomous vehicle management system 122 may determine that in order to perform the requested operation/goal safely, the current level of sensor data received by autonomous vehicle management system 122 is not sufficient”).
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to combine the teaching of using predicted operations to determine a current scenario and change an operating parameter of a sensor based on this as taught in Halder with the system taught in Ingram, the motivation being to increase safety in the system while allowing fully autonomous driving.
Independent claims 10 and 15 recite similar limitations as claim 1, and are rejected under similar rationale.
Regarding claim 5, Ingram in view of Halder teaches all the limitations of claim 1, and further teaches wherein the at least one sensor comprises a LIDAR sensor (see Ingram Figure 2, lidar sensor 120), and the at least one parameter comprises a rotational frequency of the LIDAR sensor (see Ingram paragraph [0068], wherein scan rate for lidar is well known in the art to by synonymous with rotational frequency).
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.
Claims 2, 11, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Ingram et al, U.S. Publication No. 2021/0088647 in view of Halder, U.S. Publication No. 2019/0310654 and Dong et al, U.S. Publication No. 2020/0409912.
Regarding claim 2, Ingram in view of Halder teaches all the limitations of claim 1, but does not expressively teach wherein determining the current scenario of the environment of the vehicle comprises providing the information representative of the environment of the vehicle to at least one machine learning model, wherein providing the information causes the at least one machine learning model to generate at least one output associated with the current scenario.
However, Dong in a similar invention in the same field of endeavor teaches a vehicle (see Dong Figure 1B, vehicle 152) configured to determine a current scenario of an environment of the vehicle (see Figure 1B, encode environment information step to determine scenario information step) based on at least one sensor (see paragraph [0024]) as taught in Ingram in view of Halder wherein determining the current scenario of the environment of the vehicle comprises
providing the information representative of the environment of the vehicle to at least one machine learning model (see Figure 3E, machine learning model 328 with input 327 and paragraph [0025], “The sensor data can be captured by the vehicle 301 over some period of time at pre-defined time intervals. In some embodiments, the schema encoding module 206 can analyze the captured sensor data to determine the presence of agents within the environment 300, such as a first agent vehicle 303 (“Car 1”), a second agent vehicle 304 (“Car 2”), a third agent vehicle 305 (“Car 3”), and pedestrians 306. For example, one or more machine learning models can be trained to recognize agents within the environment 300 based on the captured sensor data, such as image data capture by optical cameras of the vehicle 301, point clouds captured by a LiDAR system in the vehicle 301, and radar data captured by a radar system in the vehicle 301, to name some examples”), wherein providing the information causes the at least one machine learning model to generate at least one output associated with the current scenario (see Figure 3E, output 329 and paragraph [0028], “The machine learning model 328 can evaluate the schema-based encoding 327 to determine scenario information 329 associated with the environment during the period of time. For example, the machine learning model 328 can be trained to determine scenario families, scenario sub-families, and individual scenarios based upon an evaluation of the schema-based encoding 327”).
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to combine the teaching of using a machine learning model for analyzing the information representative of the environment as taught in Dong with the system taught in Ingram in view of Halder, the motivation being to utilize the processing capabilities and accuracy of such systems for high accuracy outputs in the vehicle.
Claims 11 and 16 recite similar limitations as claim 2, and are rejected under similar rationale.
Claims 3, 8, 12, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Ingram et al, U.S. Publication No. 2021/0088647 in view of Halder, U.S. Publication No. 2019/0310654 and Beck et al, U.S. Publication No. 2017/0153635.
Regarding claim 3, Ingram in view of Halder teaches all the limitations of claim 1, but does not expressively teach wherein determining the level of computational resources appropriate for the current scenario comprises accessing an entry of a look-up table, the entry corresponding to the current scenario, and wherein the at least one parameter is adjusted based on information associated with the entry.
However, Beck in a similar invention in the same field of endeavor teaches a vehicle (see Beck Figure 1) configured to determine a level of computational resources appropriate for a current scenario involving the vehicle and adjusting at least one parameter based on the current scenario (see paragraph [0005]) as taught in Ingram in view of Halder wherein determining the level of computational resources appropriate for the current scenario comprises
accessing an entry of a look-up table, the entry corresponding to the current scenario, and wherein the at least one parameter is adjusted based on information associated with the entry (see paragraph [0011]).
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to combine the teaching of using a look-up table for adjusting a parameter as taught in Beck with the system taught in Ingram in view of Halder, the motivation being to allow adjustments to be made to the look-up table entries based on real world data thereby allowing the system to be dynamic.
Claims 12 and 17 recite similar limitations as claim 3, and is rejected under similar rationale.
Regarding claim 8, Ingram in view of Halder teaches all the limitations of claim 1, but does not expressively teach a communications network, the operations comprising adjusting a bandwidth of the communications network based on the level of computational resources appropriate for the current scenario.
However, Beck in a similar invention in the same field of endeavor teaches a vehicle (see Beck Figure 1) configured to perform operations such as determining a level of computational resources appropriate for a current scenario involving the vehicle and adjusting at least one parameter based on the current scenario (see paragraph [0005]) as taught in Ingram in view of Halder further comprising
a communications network, the operations comprising adjusting a bandwidth of the communications network based on the level of computational resources appropriate for the current scenario (see paragraph [0011]).
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to combine the teaching of adjusting bandwidth of communications as taught in Beck with the system taught in Ingram in view of Halder, the motivation being to allow further power savings in the system via such an adjustment.
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ingram et al, U.S. Publication No. 2021/0088647 in view of Halder, U.S. Publication No. 2019/0310654 and McDermott et al, U.S. Patent No. 9,511,878.
Regarding claim 6, Ingram in view of Halder teaches all the limitations of claim 1, and further teaches wherein the at least one sensor comprises a camera (see Ingram Figure 2, other sensors 140 and paragraph [0051] as combined with Halder paragraph [0101], “After the right turn has been successfully made by autonomous vehicle 120, planning subsystem 206 may send another instruction instructing the same camera(s) to go back to communicating a different, possibly reduced, level of sensor data to autonomous vehicle management system 122”).
Ingram in view of Halder does not expressively teach the at least one parameter comprises a frame rate of the camera.
However, McDermott in a similar invention in the same field of endeavor teaches
a vehicle comprising a camera (see McDermott Abstract), wherein the vehicle
is configured to adjust at least one parameter of the camera based on
computational resources (see column 4, lines 61-67 and column 5, lines 1-5) as taught in Ingram in view of Halder wherein
the at least one parameter comprises a frame rate of the camera (see column 5,
lines 7-8).
One of ordinary skill in the art before the effective filing date of the invention
would have found it obvious as a matter of simple substitution to replace the
adjustment of the at least one parameter of the camera taught in Ingram in view of Halder with the teaching of adjusting a frame rate of a camera based on
computation resources as taught in McDermott to yield the predictable results of
successfully lowering power in the system
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Ingram et al, U.S. Publication No. 2021/0088647 in view of Halder, U.S. Publication No. 2019/0310654 and Zaidi, U.S. Publication No. 2020/0072969.
Regarding claim 7, Ingram in view of Halder teaches all the limitations of claim 1, but does not expressively teach a power supply, the operations comprising adjusting a voltage of the power supply based on the level of computational resources appropriate for the current scenario.
However, Zaidi in a similar invention in the same field of endeavor teaches a system comprising operations to control a radar system (see Zaidi Figure 6 and paragraph [0009]) that is adjusted based on a level of computation resources appropriate for a current scenario it is to operate under (see paragraph [0040]) as taught in Ingram in view of Halder further comprising
a power supply, the operations comprising adjusting a voltage of the power supply based on the level of computational resources appropriate for the current scenario (see Figure 6, power control 612 and paragraph [0040]).
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to combine the teaching of a power supply controlling power for a radar system as taught in Zaidi with the vehicle comprising a radar system with adjustable power taught in Ingram in view of Halder, the motivation being to have more direct control over individual components of the radar system thereby being able to have more granularity in what has decreased power.
Claims 9, 14, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ingram et al, U.S. Publication No. 2021/0088647 in view of Halder, U.S. Publication No. 2019/03106542 and Yoo et al, U.S. Publication No. 2020/0272149.
Regarding claim 9, Ingram in view of Halder teaches all the limitations of claim 1, but does not expressively teach the operations comprising adjusting a clock speed of the processor based on the level of computational resources appropriate for the current scenario.
However, Yoo in a similar invention in the same field of endeavor teaches a vehicle (see Yoo Figure 1 and paragraph [0023]) comprising a processor (see Figure 1, processor 112) configured to execute operations (see paragraph [0026]) based on a level of computation resources appropriate for a current scenario of the vehicle (see paragraph [0051]) as taught in Ingram in view of Halder the operations comprising
adjusting a clock speed of the processor based on the level of computational resources appropriate for the current scenario (see paragraph [0051]).
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to combine the teaching of adjusting a clock speed of a processor based on a current scenario as taught in Yoo with the system taught in Ingram in view of Halder, the motivation being to have more direct control over the processor power specifically in the system thereby being able to have more granularity in what has decreased or increased power.
Claims 14 and 19 recite similar limitations as claim 9, and is rejected under similar rationale.
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Ingram et al, U.S. Publication No. 2021/0088647 in view of Halder, U.S. Publication No. 2019/0310654 and Abdelmoneum, U.S. Publication No. 2019/0237504.
Regarding claim 20, Ingram in view of Halder teaches all the limitations of claim 1, but does not expressively teach wherein vehicle processing resources are embodied on a first system-on-chip (SoC) and vehicle battery resources are embodied on a second SoC.
However, Abdelmoneum in a similar invention in the same field of endeavor teaches a system with processing resources and battery resources (see Abdelmoneum paragraph [0142]) as taught in Ingram in view of Halder wherein
processing resources are embodied on a first system-on-chip (SoC) and battery resources are embodied on a second SoC (see paragraph [0142]).
One of ordinary skill in the art before the effective filing date of the invention would have found it obvious to combine the teaching of separate SoCs for resources as taught in Abdelmoneum with the system taught in Ingram in view of Halder, the motivation being to decentralize the system thereby easing faults when they occur.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CASEY L KRETZER whose telephone number is (571)272-5639. The examiner can normally be reached M-F 10:00-7:00 PM Pacific Time.
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/CASEY L KRETZER/Primary Examiner, Art Unit 2635
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