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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 1/26/2026 has been entered.
Information Disclosure Statement
The information disclosure statement filed 1/26/2026 fails to comply with 37 CFR 1.98(a)(3)(i) because it does not include a concise explanation of the relevance, as it is presently understood by the individual designated in 37 CFR 1.56(c) most knowledgeable about the content of the information, of each reference listed that is not in the English language. It has been placed in the application file, but the information referred to therein has not been considered. An English abstract of CN116106905A was submitted, however this is not a concise explanation of the foreign language “rejection decision” listed on the IDS.
Response to Arguments
Applicant’s arguments filed 1/26/2026 have been considered but are moot because the new grounds of rejection do 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 § 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.
Claim 3 is 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.
At the final line of claim 3, it is not clear what “the evaluating” refers to. In claim 1, a step of “evaluating against filter criteria” as well as a step of “performing an evaluation” are both introduced. The term “evaluating” matches the former, however it appears likely the latter is intended in context. Clarification is required.
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) 1-3, 5-7, 9, 22-23, 25-28, 30-32 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pyykönen et al. (WO 2023/037052) in view of Wang (CN 112327888 A).
Regarding claims 1, 22, 26-27, and 31, Pyykönen discloses a method comprising: evaluating one or more attributes of one or more radar ([0015]) detections against filter criteria (radar data outside the reference areas of grid 100 is excluded [0021]), the one or more radar detections obtained using at least one sensor of a vehicle; accumulating, based at least on the evaluating, the one or more radar detections to a zone (100) representing a defined region of an environment to compute one or more energy levels of the zone;
and determining one or more safety statuses associated with the zone based at least on one or more magnitudes of the one or more energy levels ([0027]). Pyykönen similarly discloses a processor concerning claims 22, 26-27, and 31 ([0035]).
Pyykönen illustrates the zone positioned in front of the vehicle and is also found to disclose areas 101 may cover “roads or corridors of motion” (e.g. to exclude areas such as forest next to the road, [0019]). While this appears to imply the zone may include lanes of the road itself to the side of a vehicle, Pyykönen does not expressly disclose accumulating radar detections to a zone representing a defined region of an environment, the zone positioned to a side relative to the vehicle and extending along the side in a lane adjacent to the vehicle from at least a front to at least a rear of the vehicle. Wang discloses a related autonomous vehicle navigation system and method employing a similar grid including a zone representing a defined region of an environment, the zone positioned to a side relative to the vehicle and extending along the side in a lane adjacent to the vehicle from at least a front to at least a rear of the vehicle (see Figure 1c, e.g. zone 13 alone or in combination with 11, 12, 14; EV representing the vehicle). It would have been obvious to one of ordinary skill in the art with a reasonable expectation of success to add, to the system and method of Pyykönen, defined zone(s) to accumulate radar detections including to the side in an adjacent lane as demonstrated by Wang for the conventional advantage of avoiding collisions with obstacles which are present in, or approaching to, the side via path planning (Wang [0025]: “finding a non-collision path from the initial state comprises position and attitude to the target state. In this embodiment, there is provided a path planning method…”).
It is noted the claimed “evaluation” and subsequent control is very broad and is directed to conventional autonomous driving behavior, e.g. determining a safe path based on detected objects (to include consideration of an adjacent lane). It is submitted, as Pyykönen is applied to autonomous vehicle operation ([0003], [0044]-[0045]), that while issuing a warning to the driver regarding detected humans is specified ([0027]), one of ordinary skill in the art would expect that under autonomous control the claimed evaluation and transmission of data to control the vehicle so as to avoid collision at least with humans would be present in the invention of Pyykönen. Nonetheless, while mentioning detection of humans and vehicles ([0015], [0027], [0032]) and detailing the formation of an occupancy grid ([0013], [0019]), Pyykönen provides minimal detail as to the application of such grid to autonomous driving behavior and is not found to specifically require this functionality. Wang also relates to radar occupancy grid formation for autonomous driving and discloses upon formation of the occupancy grid, performing evaluation of actions with respect to the environment including adjacent lanes (path planning) and transmitting data that causes control of the vehicle based on the evaluation (e.g. [0025]: “According to the function module of the intelligent automobile, the key technology of the intelligent automobile comprises environment perception, navigation positioning, path planning, decision control and so on. The solution mainly relates to the path planning; the path planning is intelligent vehicle information sensing and intelligent control bridge; it is the base for realizing autonomous driving. The task of the path planning is in the environment with an obstacle according to a certain evaluation standard, finding a non-collision path from the initial state comprises position and attitude to the target state”; Also note Fig. 1d). As above, it would have been obvious to one of ordinary skill in the art with a reasonable expectation of success to implement the disclosed but not detailed autonomous driving referenced by Pyykönen in the manner suggested by Wang, to include evaluating actions in adjacent lanes based on safety statuses and transmitting data to control the vehicle accordingly as claimed for the conventional advantages of finding and following a safe unoccupied path.
Regarding claim 2, Pyykönen discloses the zone comprises a grid of cells (101) dividing the defined region into grid cells that include the one or more energy levels. In combination with Wang, such cells would accordingly carry to the zone to the side of the vehicle.
Regarding claim 3, while the claim is indefinite as identified above, in combination with claim 1 as best can be determined the claim is interpreted to require accumulation of radar detections to a “zone” and a “second zone” to compute one or more energy levels of the zones, the zones representing defined regions and the zones partially overlapping to form a column positioned completely to the side relative to the vehicle, where the evaluating of actions is based on at least on one or more second energy levels of both zones. In the combination of Pyykönen in view of Wang, the “zone” may be represented by areas 12 and 13 illustrated by Wang (Fig. 1c), and the overlapping “second zone” may be represented by areas 11 and 12. In the combination, all zones are basis for evaluating actions (i.e. path planning).
Regarding claim 5, in Pyykönen as modified by Wang above to include the adjacent lane, the one or more safety statuses includes a safety status of the lane and is determined based at least on a magnitude of an energy level that represents the zone exceeding a threshold, the energy level formed from the one or more energy levels (Pyykönen [0027]).
Regarding claim 6, Pyykönen discloses defined first and second ranges of distances that have different conditions on filtering (e.g. [0019], [0022]).
Regarding claim 7, a zone of Pyykönen as modified by Wang concerning claim 1 above comprises a rectangular region that extends past the front and the rear of the vehicle (Wang Fig. 1c)
Regarding claim 9, Pyykönen discloses determining the one or more safety statuses by classifying one or more locations in the zone according to a binary classification as safe or unsafe using the energy levels (above or below a threshold, [0027]).
Regarding claims 23 and 28, Pyykönen discloses the filter criteria include in the accumulating one or more radar detections indicating one or more approaching objects (objects in the driving direction of the vehicle, e.g. [0019]).
Regarding claims 25 and 30, Pyykönen discloses the filter criteria include in the accumulating detections based on distances to the radar detections below a threshold (within grid 100, [0021]).
Regarding claim 32, in Pyykönen as modified by Wang, a control device of the vehicle prevents the vehicle from moving in a direction of the vehicle associated with the zone in the event it is occupied (i.e. the path will avoid detected obstacles, Wang [0025]).
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pyykönen in view of Wang as applied to claim 1 above, and further in view of Liu et al. (US2020/0103523).
Pyykönen and Wang do not detail particular radar sensor arrangements and therefore do not disclose respective sets of the one or more radar detections are respectively accumulated to the zone for different respective sensors of the vehicle to form respective sets of the one or more energy levels in the zone, respective safety statuses of the zone are determined for the different respective sensors using the respective sets of the one or more energy levels, and the respective safety statuses are resolved to assign the one or more safety statuses to the zone. However, at the time the application was filed it was known in the field of autonomous vehicles to use overlapping radar sensors to locate objects in a zone as shown by Liu (e.g. Figure 6), and Liu discloses, after separately accumulating radar detections of respective zones to include overlapping zones, to determine safety statuses (e.g. occupied or free) of the zone for the different respective sensors, and the safety statuses are resolved to assign one or more to the zone (Fig. 6; [0056]-[0058], e.g. “In other words, a cell of the fused radar spatial grid can be designated as being occupied when radar sensor data of the first radar sensor, the second radar sensor, or both the first and second radar sensor, indicate that the region corresponding to the cell of the spatial grid is occupied.”).
It would have been obvious to one of ordinary skill in the art with a reasonable expectation of success to further modify the method of Pyykönen to utilize multiple radar sensors with overlapping fields of view, and after separately accumulating and determining safety statuses for each, resolve the safety statuses to assign one or more to a zone as described by Liu in order to ensure continuous radar coverage of the environment and improve confidence in the occupancy determinations (Liu [0057]).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pyykönen in view of Wang as applied to claim 1 above, and further in view of Lang et al. (US 2021/0173043).
Pyykönen does not disclose applying energy levels to one or more machine learning models trained to classify a portion of the zone with one or more safety statuses. Lang discloses a vehicle radar application of machine learning where a neural network is used to distinguish between objects in a grid which can be driven over ([0033], [0011]). It would have been obvious to one of ordinary skill in the art with a reasonable expectation of success to apply machine learning to aid in determining the safety status of the locations of Pyykönen in order to correctly classify locations with objects such as manhole covers as safe ([0007, [0039]).
Claim(s) 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pyykönen in view of Wang as applied to claim 1 above, and further in view of Yamauchi et al. (US 2010/0066587).
Pyykönen does not disclose decaying energy levels over frames of radar detections. Yamauchi discloses for application to radar-equipped autonomous vehicles, affording weight to newer values by having current values in a grid decay exponentially over time ([0105]). It would have been obvious to one of ordinary skill in the art to apply decay to the energy levels of Pyykönen so that up to date information carries heavier weight for safety status determinations to adapt to the changing environment as taught by Yamauchi with predictable results.
Claim(s) 24 and 29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pyykönen in view of Wang as applied to claims 22 and 27 above, and further in view of Kellner (US 2023/0094836).
Pyykönen teaches only part of the data items of the range finding data may be allocated for accumulation, indicating a certain area of interest as one example, i.e. filtering out detections outside of an area ([0021]). Pyykönen does not disclose using Doppler velocity as another. Kellner also discloses the use of radar detections for autonomous driving where Doppler velocity is used as filter criteria, where echoes above a velocity threshold are kept and those below are filtered out ([0031]). It would have been obvious to one of ordinary skill in the art to modify the process of Pyykönen to use such a velocity filter as claimed in order to focus on reliable detection of moving targets as taught by Kellner with predictable results.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Das discloses grid formation, including adjacent lanes in an autonomous vehicle obstacle sensing environment. Louroush-Harrigan relates to using shared data to build dynamic occupancy grids.
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/MATTHEW M BARKER/ Primary Examiner, Art Unit 3646