DETAILED ACTION
Status of Claims
Claims 1-8 are currently pending and have been examined in this application. This action is FINAL.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments, see Remarks pg. 5-6, filed 12/23/2025, with respect to the objection to the title have been fully considered and are persuasive. The objection to the title has been withdrawn.
Applicant’s arguments with respect to claim(s) 1 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.
Claims 1-2 and 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. (US 20220004777 A1), in view of Hase et al. (US 20200043254 A1), and in further view of Patel et al. (US 20220315051 A1).
Regarding claim 1,
Yang teaches:
An automated driving system installed on a vehicle comprising:
a recognition sensor detecting information around the vehicle;
(Yang – [0101] “The vehicle A 10a has the image acquisition unit (the camera) 111, and for example, captures an image in a traveling direction. The captured image is inputted to the image analysis unit 112.”)
processing circuitry configured to recognize a situation around the vehicle from detection information detected by the recognition sensor and perform automated driving control based on a recognition result; and
(Yang – [0102] “The image analysis unit 112 analyzes the captured image of the image acquisition unit (the camera) 111 and performs identification processing of a body (an object) in the image. That is, body identification (object identification) is executed as to what the body being captured in each image region of the captured image is.” [0116] “For example, an automatic driving vehicle enables safe traveling by using such object identification results to perform driving control, to avoid objects that may collide in the traveling direction.” [0277] “The means and/or functions provided by the processor 91 can be provided using software stored on a tangible storage medium, a computer that executes the software, only software, only hardware, or a combination of these elements. For example, in the case where the processor 91 is provided using an electronic circuit which is hardware, this can be provide using an analog circuit or a digital circuit including multiple logic circuits.”)
one or more storage devices, wherein
the processing circuitry is further configured to execute a storing process of storing log data of the detection information in the one or more storage devices while performing the automated driving control, and
(Yang – [0093] “The controller 911 causes the regular storage medium 92 to regularly store the output value of each of the sensors 73, 77 and the switches 74 to 76 and the information acquired from each of the ECUs 20 to 70.”)
in the storing process, the processing circuitry is configured to:
specify a low reliability area around the vehicle where a reliability of the recognition result is low,
(Yang – [0170] “In this way, the low-confidence region extraction unit 114 uses the image analysis result stored in the image analysis result storage unit 113 to extract the “low-confidence region” whose object identification result is low confidence, from the captured image of the image acquisition unit (the camera) 111.”)
when the low reliability area is specified,
(Yang – [0170] “In this way, the low-confidence region extraction unit 114 uses the image analysis result stored in the image analysis result storage unit 113 to extract the “low-confidence region” whose object identification result is low confidence, from the captured image of the image acquisition unit (the camera) 111. The extracted “low-confidence region” information is inputted to an overlapping region ratio (IoU) calculation unit 131.” [0265] “The image analysis unit 112 generates pair data of a “label (a body identification result)”, which is a result of the body identification processing, and “label confidence” indicating confidence of the label in units of pixel.” [0266] “The generated data is stored in the image analysis result storage unit 113 shown in FIG. 2.”)
Yang does not explicitly disclose the following limitation, however, Hase teaches
when the low reliability area is specified, preferentially store the log data of target detection information that is the detection information related to the low reliability area.
(Hase – [0115] “As shown in FIG. 3, subsequently to the process in step S11, the controller 911 determines, on the basis of the abnormality detection result acquired from each of the ECUs 20 to 70, whether the vehicle 10 has an abnormality, as a process in step S12. When an affirmativ0e determination is made in the process in step S12, that is, when the vehicle 10 has an abnormality, when the controller 911 copies the data stored in the regular storage medium 92 to each of the one or more saving storage media 93 as a process in step S13.” [0117] “As shown in FIG. 3, when step S13 is performed, the controller 911 brings a series of processes to an end. Also when a negative determination is made in the process in step S12, that is, when the vehicle 10 has no abnormality, the controller 911 brings a series of processes to an end.”)
Yang and Hase are both considered to be analogous to the claimed invention because they are in the same field of controlling an autonomous vehicle based on the sensor results. It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to combine Yang and Hase to include preferentially storing abnormality data in order to easily analyze the determination information stored in the saving storage media (Hase, para. [0120]).
The combination of Yang and Hase does not explicitly teach the following limitation, however, Patel teaches:
the reliability of the recognition result is based on a probability of each recognition result in a statistical model;
(Patel – [0121] “In some variations, for instance, S230 includes performing an analysis (e.g., probabilistic analysis, statistical analysis, inference process, processing with a trained model, etc.) which functions to determine a likelihood (e.g., probability, confidence, distribution, etc.) associated with any or all of: any virtual object being in the blind region; a particular type of virtual object being in the blind region; and/or the parameters (e.g., speed) associated with a virtual object in the blind region.”)
Patel is considered to be analogous to the claimed invention because it is in the same field of monitoring the sensor readings around an autonomous vehicle. It would have been obvious to one skilled in the art before the effective filing date of claimed invention to modify the combination of Yang and Hase with Patel to include a statistical model in order to create an improved method for operating an autonomous vehicle with an incomplete understanding of its environment (Patel, para. [0004]).
Regarding claim 2,
The combination of Yang, Hase, and Patel teaches the limitations of claim 1.
Hase further teaches:
wherein
in the storing process, the processing circuitry is configured to:
acquire a specific recognition result that is the recognition result involved in a calculation of a control amount of the automated driving control; and
(Hase – [0060] “The autonomous driving ECU 70 performs an autonomous driving control on the basis of various kinds of information acquired from the ECUs 20, 30, 40, 50, 60, the surrounding recognition sensor 71, the input device 72, the travel information sensor 73, the car navigation device 78, and the like.” [0179] “As indicated by the dashed line in FIG. 2, the processor 91 further includes a travel condition detector 912. On the basis of various kinds of information acquired from the ECUs 20 to 70, the travel condition detector 912 detects a vehicle travel condition such as a traffic lane in which the vehicle 10 is traveling and the state of a road surface on which the vehicle 10 is traveling.”)
store the log data of information related to the specific recognition result among the target detection information with higher priority.
(Hase – [0180] “When determining that the travel condition of the vehicle 10 detected by the travel condition detector 912 needs to be analyzed with high priority, the controller 911 according to the present variation shortens the sampling interval of data in the regular storage medium 92 and the saving storage medium 93 or extends the sampling period of data in the regular storage medium 92 and the saving storage medium 93.”)
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to combine Yang and Hase to include storing data at a higher priority in order to easily analyze the determination information stored in the saving storage media (Hase, para. [0120]).
Regarding claim 5,
The combination of Yang, Hase, and Patel teaches the limitations of claim 1.
Patel further teaches:
wherein the statistical model is a rule-based model.
(Patel – [0124] “In a preferred set of variations, the analyses are performed with a set of probabilistic models, algorithms, and/or equations (e.g., untrained and/or unlearned models, trained and/or learned models, rule-based models, programmed models, etc.).”)
It would have been obvious to one skilled in the art before the effective filing date of claimed invention to modify the combination of Yang and Hase with Patel to include a statistical model in order to create an improved method for operating an autonomous vehicle with an incomplete understanding of its environment (Patel, para. [0004]).
Regarding claim 6,
The combination of Yang, Hase, and Patel teaches the limitations of claim 1.
Yang further teaches:
wherein the low reliability area comprises an area including the recognition result whose reliability is less than or equal to a predetermined threshold value.
(Yang – [0154] “Note that in a case where the region of (2) described above is selected, that is, [0155] (2) a region where the label confidence is less than the specified threshold value (Th1), [0156] this region is selected, the label confidence (conf.sub.sema) to be compared with the threshold value (Th1) is calculated in accordance with one of processing examples (Processing example 1) and (Processing example 2) shown in FIG. 6.”)
Regarding claim 7,
The combination of Yang, Hase, and Patel teaches the limitations of claim 1.
Hase further teaches:
wherein the processing circuitry is configured to only store the log data of the target detection information that is the detection information related to the low reliability area.
(Hase – [0115] “As shown in FIG. 3, subsequently to the process in step S11, the controller 911 determines, on the basis of the abnormality detection result acquired from each of the ECUs 20 to 70, whether the vehicle 10 has an abnormality, as a process in step S12. When an affirmativ0e determination is made in the process in step S12, that is, when the vehicle 10 has an abnormality, when the controller 911 copies the data stored in the regular storage medium 92 to each of the one or more saving storage media 93 as a process in step S13.” [0117] “As shown in FIG. 3, when step S13 is performed, the controller 911 brings a series of processes to an end. Also when a negative determination is made in the process in step S12, that is, when the vehicle 10 has no abnormality, the controller 911 brings a series of processes to an end.”)
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to combine Yang and Hase to include preferentially storing abnormality data in order to easily analyze the determination information stored in the saving storage media (Hase, para. [0120]).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. (US 20220004777 A1), in view of Hase et al. (US 20200043254 A1), in further view of Patel et al. (US 20220315051 A1), and in further view of Bangalore Ramaiah et al. (US 20220350995 A1).
Regarding claim 3,
The combination of Yang, Hase, and Patel teaches the limitations of claim 1.
The combination of Yang, Hase, and Patel does not explicitly teach the following limitations, however, Bangalore Ramaiah teaches:
wherein
in the storing process, the processing circuitry is configured to:
compress the detection information and store the compressed detection information as the log data; and
preferentially store the log data of the target detection information by setting a compression rate of the target detection information lower than that of other detection information.
(Bangalore Ramaiah – [0114] “In addition, the images herein may be compressed. However, some compression algorithms may result in loss of information, which may be undesirable for higher priority areas. Accordingly, the system herein may determine an optimal compression level and corresponding compression algorithm to use for the individual selected areas based at least on an indicated priority level for each area.” [Claim 3] “The system as recited in claim 1, the operations further comprising: segmenting the image into at least one higher priority area and a least one lower priority area based at least in part on the at least one of the historical information or the road anomaly information; and compressing the at least one higher priority area with a lower compression rate than a compression rate used for compressing the at least one lower priority area.”)
Bangalore Ramaiah is considered to be analogous to the claimed invention because it is in the same field analyzing the accuracy of sensor information. It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to modify the combination of Yang, Hase, and Patel with Bangalore Ramaiah to include setting a compression rate for storing the image data in order to reduce the memory requirements and improve the depth estimation for all obstacles, road anomalies, and other features in all likely scenarios (Bangalore Ramaiah, para. [0054]).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. (US 20220004777 A1), in view of Hase et al. (US 20200043254 A1), in further view of Patel et al. (US 20220315051 A1), and in further view of Moor et al. (US 11378523 B1).
Regarding claim 4,
The combination of Yang, Hase, and Patel teaches the limitations of claim 1.
The combination of Yang, Hase, and Patel does not explicitly teach the following limitations, however, Moor teaches:
wherein
in the storing process, the processing circuitry is configured to:
generate reproduction data for reproducing the detection information in a pseudo manner; and store the reproduction data as the log data.
(Moor – [Col. 8 line 66 – Col. 9 line 16] “In certain examples, the blemish detection system may perform initial modifications to the image at this stage. For example, if a lens of the optical sensor has a focal length that is below a threshold causing a wide angle view, for example, a fisheye lens, the system may remove parts of the image that correspond to areas outside of the field of view of the lens. For example, a radius of an image corresponding to field of view of the lens may be selected and information outside of the radius is removed.”)
Moor is considered to be analogous to the claimed invention because it is in the same field of storing data from sensors on an autonomous vehicle. It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to modify the combination of Yang, Hase, and Patel with Moor to include partially duplicate the image data in order to generate data representing an environment with a high degree of accuracy and precision about the environment while providing the desired field of view coverage of the vehicle (Moor, [Col. 13 lines 16-28]).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. (US 20220004777 A1), in view of Hase et al. (US 20200043254 A1), in further view of Patel et al. (US 20220315051 A1), and in further view of Tanaka et al. (US 20100088541 A1).
Regarding claim 8,
The combination of Yang, Hase, and Patel teaches the limitations of claim 1.
The combination of Yang, Hase, and Patel does not explicitly teach the following limitations, however, Tanaka teaches:
wherein the processing circuitry is configured to switch a method of storing the log data of the target detection information based on a free capacity of the one or more storage devices.
(Tanaka – [0098] “When there are free spaces in a plurality of upper storage areas, or when there are a plurality of free lower storage areas, a free lower storage area is selected from the upper storage area with the largest size, for example. When there are a plurality of free lower storage areas in the selected upper storage area, the lower storage areas to be assigned are selected in the order of the addresses of the lower storage areas, for example.”)
Tanaka is considered to be analogous to the claimed invention because it is in the same field of controlling the storing of data. It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to modify the combination of Yang, Hase, and Patel with Tanaka in order to prevent information from being overwritten by new information and ensure all important information is stored (Tanaka, para. [0023]-[0024]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure or directed to the state of the art is listed on the enclosed PTO-892.
The following is a brief description for relevant prior art that was cited but not applied:
Horita et al. (US 20230182732 A1) discloses a detectable zone is dynamically calculated by performing statistical analysis using information on the detection position and the detection reliability included in the detection information of the external environment sensor.
Matthaei et al. (US 20230334836 A1) discloses determining a reliability region regarding each object detection by at least one environment perception sensor, and confining the sensor fusion of the object detections to the reliability region, wherein outside the reliability region, object localization takes place on the basis of the object detections by the at least one environment perception sensor to which the determined reliability region does not apply.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MELANIE HUBER whose telephone number is (703)756-1765. The examiner can normally be reached M-F 7:30am-4pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, JAMES LEE can be reached at (571)-270-5965. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/M.G.H./Examiner, Art Unit 3668 Supervisory Patent Examiner, Art Unit 3668/JAMES J LEE/